{"cssClassNames":"page basicpage summit-page","clientlibsAsync":false,"dataLayerClientlibIncluded":true,"dataLayerName":"adobeDataLayer","templateName":"quickstart-page-template","designPath":"/libs/settings/wcm/designs/default","brandSlug":"","componentsResourceTypes":["snowflake-site/components/quickstart/quickstart-button","snowflake-site/components/nav/nav-column/nav-column-container","snowflake-site/components/structure/page","snowflake-site/components/button","snowflake-site/components/quickstart/quickstart-hero","snowflake-site/components/quickstart/quickstart-table-of-content","snowflake-site/components/experiencefragment","snowflake-site/components/mega-header","snowflake-site/components/modal/modal-container","snowflake-site/components/image","snowflake-site/components/nav/nav-dropdown-header","snowflake-site/components/wistia-video/cta","nt:folder","snowflake-site/components/container","snowflake-site/components/nav/nav-dropdown-menu","snowflake-site/components/nav/nav-column","snowflake-site/components/flexible-column-container","snowflake-site/components/quickstart/quickstart-table-of-content/quickstart-table-of-content-container","snowflake-site/components/button/embedded","snowflake-site/components/icon","snowflake-site/components/nav/nav-mega","cq:LiveCopy","snowflake-site/components/quickstart/quickstart-last-modified","snowflake-site/components/nav/nav-promo-section","snowflake-site/components/markup-editor","snowflake-site/components/text","snowflake-site/components/title-v2","snowflake-site/components/nav/nav-dropdown-footer","nt:unstructured","nt:file","snowflake-site/components/contentfragment","snowflake-site/components/nav/nav-item","snowflake-site/components/nav/nav-promo-card","snowflake-site/components/form/marketo-v2","snowflake-site/components/nav/language-navigation","snowflake-site/components/title","wcm/foundation/components/responsivegrid","nt:resource","snowflake-site/components/structure/xfpage","snowflake-site/components/flexible-column-container/flexible-column-content-container","snowflake-site/components/pushdown-banner"],"allowedRenditionsWidth":["320","480","640","768","960","1200","1440","1920"],"description":"Build data engineering pipelines using Snowflake Notebooks with Python and SQL for interactive, collaborative pipeline development.","lastModifiedDate":1781813082882,"language":"en","title":"Getting Started with Data Engineering using Snowflake Notebooks","tags":["snowflake-site:taxonomy/solution-center/certification/quickstart","snowflake-site:taxonomy/solution-center/certification/community-sourced","snowflake-site:taxonomy/solution-center/includes/architecture","snowflake-site:taxonomy/product/data-engineering"],"analyticsPageType":"quickstart-page-template","analyticsCategory":"general","analyticsSubCategory":"","excludeFromAnalytics":false,"analyticsDebugMode":false,"analyticsData":{"excludeFromAnalytics":false,"subCategory":"","pageType":"quickstart-page-template","templateName":"quickstart-page-template","siteName":"snowflake","pageUrl":"/content/snowflake-site/global/en/developers/guides/data-engineering-with-notebooks","language":"en","category":"general","pageName":"Getting Started with Data Engineering using Snowflake Notebooks","contentTags":["snowflake-site:taxonomy/solution-center/certification/quickstart","snowflake-site:taxonomy/solution-center/certification/community-sourced","snowflake-site:taxonomy/solution-center/includes/architecture","snowflake-site:taxonomy/product/data-engineering"]},":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"markup_editor_1950346551":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-banner":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-header":"aem-GridColumn aem-GridColumn--default--12","responsivegrid":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-footer":"aem-GridColumn aem-GridColumn--default--12","modal_container":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"columnCount":12,":items":{"experiencefragment-banner":{"id":"experiencefragment-0ba59a9fde","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/pushdown-banner/master/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"pushdown_banner_copy":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-f01a44d534",":items":{"pushdown_banner_copy":{"id":"pushdown-banner-a343afba1f","contentHeadline":"Summit Builder Keynote Debut","contentDescription":"Broadcast live on June 23","contentJustifyContent":"center","linkStyle":"text-white","linkCTA":{"id":"link-cta","heapButtonClasses":["pushdown_banner"],"showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://reg.snowflake.com/flow/snowflake/summit26/digitalreg/page/main"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Register now"},":type":"snowflake-site/components/pushdown-banner","appliedCssClassNames":"snowflake-pushdown-banner-text-white snowflake-pushdown-banner-background-black"}},":itemsOrder":["pushdown_banner_copy"],":type":"snowflake-site/components/container"},"image":{":type":"nt:unstructured"},"cq:metadata":{":type":"nt:unstructured"}},":itemsOrder":["root","image","cq:metadata"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"experiencefragment-header":{"id":"experiencefragment-4758ab9ef9","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"mega_header":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-dd0939b9a4",":items":{"markup_editor":{"id":"markup-editor-f8f14f6e0a","title":" ","cssContent":".footer-nav__link-group .snowflake-button-container,.subnav__item--button,.snowflake-card-v2-advanced-button .snowflake-button-container{justify-content:flex-start}.mega-nav__sign-in.snowflake-button-container{display:none}@media screen and (min-width:768px){.mega-nav__sign-in.snowflake-button-container{display:inline-block;font-family:'Texta',sans-serif;font-weight:800 !important}}@media screen and (min-width:1024px) and (max-width:1199px){.snowflake-mega-nav-header-buttons-container .snowflake-button-blue .snowflake-button-container{font-size:13px !important}.snowflake-language-navigation .language-icon{width:18px !important;height:18px !important;margin-right:4px !important}}.mega-nav__sign-in svg{display:none}.nav-item__platform-parent-why-sf.snowflake-mega-nav-nav-item\u003Ea:hover,.nav-item__platform-parent.snowflake-mega-nav-nav-item\u003Ea:hover{background-color:transparent !important}.nav-platform-sidebar .snowflake-mega-nav-nav-item:hover.blue-icon .snowflake-mega-nav-nav-item-icon__inner{background-color:var(--ui-01) !important}@media screen and (min-width:1024px){.snowflake-mega-nav-navigation-dropdown{overflow:hidden}.meganav-platform-features{padding-left:64px}.meganav-platform-features::before{content:'';transform:translateX(-64px);display:block;z-index:0;width:100%;height:100%;position:absolute;top:0;background:#f7f9fa}.nav-item--si.snowflake-mega-nav-nav-item\u003Ea:hover{background-color:transparent}.nav-item--si{border-bottom:1px solid #ccc;padding-bottom:16px;margin-bottom:8px}.nav-item__platform-parent{border-bottom:1px solid #ccc;margin-bottom:8px;padding-bottom:16px}.nav-item__platform-parent-why-sf .snowflake-mega-nav-nav-item-description::after{content:'What Snowflake can do for you \u003E';display:block;color:var(--ui-01);margin-top:16px}.nav-item__platform-parent .snowflake-mega-nav-nav-item-description::after{content:'View the platform \u003E';display:block;color:var(--ui-01);margin-top:16px}}@media screen and (min-width:1367px){.snowflake-mega-nav-nav-item-description{font-size:13px !important;line-height:20px !important}.snowflake-mega-nav-nav-item-title-wrapper\u003E.snowflake-mega-nav-nav-item-title{font-size:17px !important}.nav-item__platform-parent-why-sf .snowflake-mega-nav-nav-item-title,.nav-item__platform-parent .snowflake-mega-nav-nav-item-title{font-size:24px !important;line-height:32px !important;margin-bottom:8px !important}.nav-item__platform-parent-why-sf .snowflake-mega-nav-nav-item-description,.nav-item__platform-parent .snowflake-mega-nav-nav-item-description{font-size:14px !important;line-height:20px !important}}html.wf-texta-n9-loading .display-1-v2{font-size:48px!important;line-height:50px!important;letter-spacing:-.5px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .heading-4-v2{font-size:18px!important;line-height:24px!important;font-family:sans-serif!important}@media screen and (min-width:768px){html.wf-texta-n9-loading .display-2-v2{font-size:48px!important;line-height:50px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .display-1-v2{font-size:55.5px!important;line-height:54px!important;letter-spacing:-.5px!important;font-family:sans-serif!important}html.wf-lato-n4-loading .body-2,html.wf-lato-n4-loading .heading-5-v2,html.wf-lato-n4-loading .snowflake-card-v2-advanced-text .snowflake-text p{font-size:15.5px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .heading-2,html.wf-texta-n9-loading .heading-2-v2{font-size:34px!important;line-height:38px!important;letter-spacing:-.75px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .heading-6-v2.snowflake-mega-nav-navigation-title{font-size:13.5px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .heading-4,html.wf-texta-n8-loading .snowflake-button-container,html.wf-texta-n8-loading .snowflake-button-regular .snowflake-button-container{font-size:13px!important;line-height:20px!important;letter-spacing:.25px!important;font-family:sans-serif!important}}@media screen and (min-width:1024px){html.wf-lato-n4-loading .snowflake-mega-nav-nav-item-description{font-size:11.5px!important;font-family:sans-serif!important}html.wf-lato-n4-loading .body-2,html.wf-lato-n4-loading .text-size-regular .snowflake-text li,html.wf-lato-n4-loading .text-size-regular .snowflake-text p,html.wf-lato-n4-loading .text-size-regular .snowflake-text span[data-testid=text-content],html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom li,html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom p,html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom span[data-testid=text-content]{font-size:13.5px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .snowflake-button-compact .snowflake-button-container{font-size:12px!important;letter-spacing:0!important;line-height:18px!important}}@media screen and (min-width:1367px){html.wf-lato-n4-loading .hp-hero__eyebrow a\u003Eb:first-child{font-size:11px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .hp-hero__eyebrow a{font-size:13px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .display-2-v2{font-size:61px!important;line-height:60px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .display-1-v2{font-size:74.5px!important;line-height:74px!important;letter-spacing:-.75px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .heading-2,html.wf-texta-n9-loading .heading-2-v2{font-size:41px!important;letter-spacing:-.75px!important;font-family:sans-serif!important}html.wf-texta-n9-loading .heading-3-v2{font-family:sans-serif!important;letter-spacing:-.75px!important;font-size:33.75px!important}html.wf-texta-n9-loading .heading-4-v2{font-size:19.5px!important;line-height:26px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .heading-6-v2{font-size:12px!important;font-family:sans-serif!important}html.wf-texta-n8-loading .heading-6-v2.snowflake-mega-nav-navigation-title{font-size:14px!important;font-family:sans-serif!important}html.wf-lato-n4-loading .body-1,html.wf-lato-n4-loading .cq-Editable-dom[data-cq-data-path*=text] ol\u003Eli,html.wf-lato-n4-loading .snowflake-text li,html.wf-lato-n4-loading .snowflake-text p,html.wf-lato-n4-loading .text-size-large .snowflake-text li,html.wf-lato-n4-loading .text-size-large .snowflake-text p,html.wf-lato-n4-loading .text-size-large .snowflake-text span[data-testid=text-content],html.wf-lato-n4-loading .text-size-large.cq-Editable-dom li,html.wf-lato-n4-loading .text-size-large.cq-Editable-dom p,html.wf-lato-n4-loading .text-size-large.cq-Editable-dom span[data-testid=text-content],html.wf-lato-n4-loading.cq-Editable-dom[data-cq-data-path*=text]\u003Ep,html.wf-lato-n4-loading.cq-Editable-dom[data-cq-data-path*=text]\u003Eul\u003Eli{font-size:17.5px!important;font-family:sans-serif!important}html.wf-lato-n4-loading .body-2,html.wf-lato-n4-loading .text-size-regular .snowflake-text li,html.wf-lato-n4-loading .text-size-regular .snowflake-text p,html.wf-lato-n4-loading .text-size-regular .snowflake-text span[data-testid=text-content],html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom li,html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom p,html.wf-lato-n4-loading .text-size-regular.cq-Editable-dom span[data-testid=text-content],html.wf-texta-n8-loading .snowflake-button-link .snowflake-button-container,html.wf-texta-n8-loading .snowflake-button-link-back .snowflake-button-container{font-size:15.5px!important;font-family:sans-serif!important}html.wf-lato-n4-loading .body-3,html.wf-lato-n4-loading .text-size-small .snowflake-text li,html.wf-lato-n4-loading .text-size-small .snowflake-text p,html.wf-lato-n4-loading .text-size-small .snowflake-text span[data-testid=text-content],html.wf-lato-n4-loading .text-size-small.cq-Editable-dom li,html.wf-lato-n4-loading .text-size-small.cq-Editable-dom p,html.wf-lato-n4-loading .text-size-small.cq-Editable-dom span[data-testid=text-content]{font-size:13.5px!important;font-family:sans-serif!important}}#industryPlatformSection,.sc-hero{background-position:top left;background-size:20% auto}.bwalignc,.bwalignr{list-style-position:inside}.snowflake-text p sup{font-size:10px}#industryPlatformSection .industry-platform__row .snowflake-flexible-column-container-items,.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container,.snowflake-hero-system-content-container{gap:16px}.agenda-item p,.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv,.partner-details p{margin:0!important}.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container::after,.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container::before,.hide-logo .snowflake-case-study-card-logo,.partner-page__powered-by-logo,.sc-hero div.code-toolbar\u003E.toolbar,.snowflake-card-v2-advanced.no-link .snowflake-card-v2-advanced-button,.snowflake-partner-hero-card-badge-container{display:none!important}.section--card-mobile-carousel .snowflake-flexible-column-container-items-with-carousel{max-width:100%!important}@media screen and (min-width:768px){.button-group-pair .snowflake-button-container.inline-button--desktop,.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:auto!important;display:inline-block!important}.button-group-pair\u003E.container\u003E.cmp-container\u003E.aem-container{align-items:center;justify-content:flex-start!important}.button-group-pair.center\u003E.container\u003E.cmp-container\u003E.aem-container{justify-content:center!important}.section--card-mobile-carousel{margin-left:var(--tablet-portrait-margin,48px)!important;margin-right:var(--tablet-portrait-margin,48px);width:calc(100% - 96px)!important;width:calc(100% - var(--tablet-portrait-margin) * 2)!important}}@media screen and (min-width:1024px){.section--card-mobile-carousel{margin-left:var(--tablet-horizontal-margin,48px)!important;margin-right:var(--tablet-horizontal-margin,48px);width:calc(100% - 96px)!important;width:calc(100% - var(--tablet-horizontal-margin) * 2)!important}.snowflake-mega-nav-header-mobile-icon{display:none!important}}@media screen and (min-width:1367px){.section--card-mobile-carousel{margin-left:var(--desktop-margin,6.5%)!important;margin-right:var(--desktop-margin,6.5%);width:87%!important;width:calc(100% - var(--desktop-margin) * 2)!important}.logo-container{min-width:143px}.sc-hero__headline .heading-1-v2{font-size:60px}.snowflake-mega-nav-navigation-title{font-size:17px}.snowflake-mega-nav-dropdown-footer-wrapper .snowflake-title-v2 .snowflake-title-v2-line:first-child{font-size:16px!important;line-height:24px!important}}.hero--home{overflow:hidden;background-color:var(--ui-01);z-index:2}.hp-hero__subheadline{width:90%}.hero--home .snowflake-button-container{transition:.3s}.hero--home .snowflake-button-primary a:hover,.hero--home .snowflake-button-secondary a:hover,.hero--home .snowflake-button-white a:hover{transition:.3s;background-color:var(--ui-02)!important;color:var(--ui-05)!important}.hero--home .snowflake-button-secondary a:hover{border-color:var(--ui-05)!important}.hero--home .snowflake-button-primary a:hover,.hero--home .snowflake-button-white a:hover{border-color:var(--ui-02)!important}.bwalignc,.hp-hero__eyebrow{text-align:center}.hp-hero__eyebrow a{display:inline-flex;flex-direction:column;justify-content:center;cursor:pointer;padding:8px;border-radius:var(--spacing-01);gap:8px;align-items:center;background-color:#45aee3;color:var(--ui-03);font-family:Texta,sans-serif;font-weight:800;font-size:16px;line-height:22px;transition:background-color .3s}.hp-hero__eyebrow a:hover{background-color:#7fc6ea;text-decoration:none;transition:background-color .3s}.hp-hero__eyebrow a\u003Eb:first-child{text-transform:uppercase;white-space:nowrap;display:inline-block;background-color:var(--ui-02);color:var(--ui-05);font-size:12px!important;line-height:16px!important;font-family:Lato,sans-serif;font-weight:500!important;padding:3px 6px;border-radius:2px;letter-spacing:1px}@media screen and (min-width:767px){.hp-hero__eyebrow{text-align:left}.hp-hero__eyebrow a{flex-direction:row;text-align:left}}.hero--home__inner .offset-video,.hero--home__inner .snowflake-experience-fragment,.offset-video__bg-image{max-height:200px;overflow:hidden}.hero--home__inner .offset-video .wistia-responsive-padding{padding-top:100%}.hero--home__inner .snowflake-experience-fragment,.offset-video__bg-image{position:absolute!important;top:0;left:0;width:100%}.offset-video__bg-image{z-index:-1}@media screen and (min-width:768px){.hero--home__inner .snowflake-experience-fragment,.offset-video,.offset-video__bg-image{position:absolute!important;max-height:none;top:0;left:0;width:250%;padding-bottom:250%;transform:translate(0,-50%);height:0}.workloads_7.unistore{max-width:317px}}.promo-banner--homepage{z-index:2}.homepage-banner-offset-container::after{content:\"\";display:block;position:absolute;bottom:0;z-index:1;left:0;width:100%;height:80%;background:#fff}.section--quicklinks .snowflake-button-full-width a{padding-left:24px!important;padding-right:24px!important;transition:box-shadow .25s cubic-bezier(.4,0,.2,1);text-align:left;display:flex;justify-content:center;align-items:center}.section--quicklinks .snowflake-button-full-width a:hover{box-shadow:0 16px 16px 0 rgb(0 0 0 / .16);transition:box-shadow .25s cubic-bezier(.4,0,.2,1)}.section--quicklinks .snowflake-button-container:focus-visible a::before,.section--quicklinks .snowflake-button-full-width a::before{content:\"\";width:23px;height:23px;flex-shrink:0;margin-right:12px;display:inline-block;background-size:cover;background-repeat:no-repeat;background-position:center}#industryPartnerSlider .snowflake-navigation-icon.swiper-button-disabled,#partnerResources .section--resource-hub a svg,.button-tabs span.snowflake-tabs-navigation-item:after,.customer-card--hide-cta .snowflake-case-study-card-button,.dot-tabs span.snowflake-tabs-navigation-item::after,.partner-sidebar__mobile-expand,html:not(.aem-AuthorLayer-initial):not(.aem-AuthorLayer-Edit) .tab-content:not(.is-active){display:none}.section--quicklinks .snowflake-button-full-width a.pricing::before{background-image:url(https://www.snowflake.com/content/dam/snowflake-site/general/icons/decorative-icons/pricing-icon.svg)}.section--quicklinks .snowflake-button-full-width a.snowflake_on_snowflake::before{background-image:url(https://www.snowflake.com/content/dam/snowflake-site/general/icons/navigation/nav-icon_snowflake-bug.svg)}.section--quicklinks .snowflake-button-full-width a.virtual_hands_on_labs::before{background-image:url(https://www.snowflake.com/content/dam/snowflake-site/general/icons/navigation/nav-icon__training.svg)}.section--quicklinks .snowflake-button-full-width a.weekly_demo::before{background-image:url(https://www.snowflake.com/content/dam/snowflake-site/general/icons/navigation/nav-icon__webinars.svg)}@media screen and (min-width:1024px){.hero--home__inner .snowflake-experience-fragment,.offset-video,.offset-video__bg-image{left:-50%}.section--quicklinks .snowflake-flexible-column-container-items{gap:24px}.snowflake-quote-item-inner{padding:32px 24px 24px!important}}#communitiesOuter_overflowBottomGray::after{max-height:100px}#caseStudyOuter_overflowBottomMidBlue::after{max-height:180px}#caseStudyInner .snowflake-case-study-card .snowflake-wistia-video{border-radius:0!important}#caseStudyInner .snowflake-case-study-card{box-shadow:none!important;border-radius:0}#caseStudyInner{max-width:1200px;margin:0 auto;box-shadow:rgb(152 162 179 / .1) 0 10px 20px 0,rgb(152 162 179 / .25) 0 2px 6px 0;border-radius:8px;overflow:hidden;position:relative;z-index:1}.case-study__logo-bar\u003E.snowflake-flexible-column-container-items{background:#f7f9fa;padding:32px 16px 40px}.case-study__logo-bar .cmp-image__image{width:90%;margin:0 auto;max-width:240px}.hp-platform__text-group\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:not(:first-child),.sc-sidebar__group .snowflake-button-link{margin-top:8px}.workloads_7.unistore{margin-left:auto;margin-right:auto}#homepageFootnotesInner .snowflake-simple-stat-disclaimer .snowflake-text p{color:#fff!important}.snowflake-simple-stat-disclaimer .snowflake-text p\u003Ea{border-bottom:1px solid var(--ui-03);color:var(--text-03)}.snowflake-card-v2-advanced{color:inherit}#workloadCardGridOuter .snowflake-card-v2-base-front{gap:0}.video-modal.snowflake-modal-window-open-inner{background-color:#fff0;padding:8px;border:none}.snowflake-container-arrow-dotted-faded .snowflake-container-arrow-dotted-faded-image{width:40%!important;max-width:420px;top:4%!important}.list--blue-bullets ul{margin:0!important;padding:0!important;list-style-type:none}.list--blue-bullets li{margin:0;padding:0 0 0 32px;position:relative}.list--blue-bullets li::before{content:\"\";display:block;border-radius:100%;background:#29b5e8;width:18px;height:18px;position:absolute;top:4px;left:0;border:5px solid #e5f2f7;box-sizing:border-box}.list--blue-bullets li:not(:last-child){margin-bottom:1rem}.logo-tabs .snowflake-navigation-container,.snowflake-simple-stat-content:empty,.summit-speaker-card .snowflake-card-v2-advanced-text{margin-bottom:0}#techResourceInner,#techResourceOuter,div.overflow-bottom--blue,div.overflow-bottom--gray,div.overflow-bottom--mid-blue,div.overflow-bottom--white,div.overflow-top--blue,div.overflow-top--gray,div.overflow-top--mid-blue,div.overflow-top--white,div[id$=overflowBottomGray],div[id$=overflowBottomMidBlue],div[id$=overflowTopBlue],div[id$=overflowTopGray]{position:relative}div.overflow-bottom--blue::after,div.overflow-bottom--gray::after,div.overflow-bottom--mid-blue::after,div.overflow-bottom--white::after,div.overflow-top--blue::after,div.overflow-top--gray::after,div.overflow-top--mid-blue::after,div.overflow-top--white::after,div[id$=overflowBottomGray]::after,div[id$=overflowBottomMidBlue]::after,div[id$=overflowBottomWhite]::after,div[id$=overflowTopBlue]::after,div[id$=overflowTopGray]::after,div[id$=overflowTopWhite]::after{content:\"\";display:block;position:absolute;left:0;width:100%;height:40%}div.overflow-top--blue::after,div.overflow-top--gray::after,div.overflow-top--mid-blue::after,div.overflow-top--white::after,div[id$=overflowTopBlue]::after,div[id$=overflowTopGray]::after,div[id$=overflowTopWhite]::after{top:0}div.overflow-bottom--blue::after,div.overflow-bottom--gray::after,div.overflow-bottom--mid-blue::after,div.overflow-bottom--white::after,div[id$=overflowBottomGray]::after,div[id$=overflowBottomMidBlue]::after,div[id$=overflowBottomWhite]::after{bottom:0}div.overflow-bottom--white::after,div.overflow-top--white::after,div[id$=overflowBottomWhite]::after,div[id$=overflowTopWhite]::after{background:#fff!important}div.overflow-bottom--gray::after,div.overflow-top--gray::after,div[id$=overflowBottomGray]::after,div[id$=overflowTopGray]::after{background:#f6f9fa!important}div.overflow-bottom--mid-blue::after,div.overflow-top--mid-blue::after,div[id$=overflowBottomMidBlue]::after,div[id$=overflowTopMidBlue]::after{background:#11567f!important}div.overflow-bottom--blue::after,div.overflow-top--blue::after,div[id$=overflowBottomBlue]::after,div[id$=overflowTopBlue]::after{background:#259edc!important}.snowflake-premium-content-banner.promo-banner--no-shadow{box-shadow:none!important}#industryPartnerSlider .cmp-image__image,#industryPartnerSlider .section--partner-tabs .snowflake-image-container .cmp-image__image,#partnerSidebar,.has-shadow .cmp-image__image{box-shadow:0 10px 20px 0 rgb(152 162 179 / .1),0 2px 6px 0 rgb(152 162 179 / .25)}.content-chip--has-desc{align-items:flex-start;padding:20px!important}.content-chip--has-desc .snowflake-content-chip-image{max-width:100px}.content-chip--has-desc .snowflake-content-chip-image__image{aspect-ratio:1}.content-chip--has-desc .snowflake-title-v2-line:first-child{font-size:18px!important}.content-chip--has-desc .snowflake-title-v2-line:nth-child(2){color:#000!important;font-weight:500!important;font-size:16px!important;line-height:22px!important;margin-top:2px!important}.content-chip--has-desc .snowflake-content-chip-button{margin-top:6px!important;font-size:18px!important;display:none}.square-image .snowflake-content-chip-image{aspect-ratio:1;max-width:120px}.section--logo-bar.smaller-logos .snowflake-image-container .cmp-image__image{max-width:200px;margin:0 auto}.snowflake-card-v2-advanced-tag,.snowflake-content-chip-tag{padding:3px 6px!important}.sc-overview__webinar-promo-banner .snowflake-content-chip-button,.snowflake-card-v2-advanced-title:first-child,.summit-pricing-block__aside ul{margin-top:0}.dot-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item{width:40px;height:40px;display:flex;justify-content:center;align-items:center;margin:0!important}.dot-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item p{width:12px;height:12px;background:var(--ui-12);border-radius:100%}.dot-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item p,.logo-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item p{font-size:0!important}.dot-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item.active p{background:var(--ui-01)}.button-tabs .snowflake-navigation-container .swiper-wrapper{padding:8px 0}.button-tabs .snowflake-navigation-container .swiper-slide{margin:0 6px}.button-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item{padding:8px 24px;background-color:#f6f9fa;border-radius:48px;margin:0}.button-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item p{text-transform:uppercase;font-family:Texta,sans-serif;font-weight:700}.button-tabs .border-top{border-top:1px solid #ccc}.button-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item.active{background-color:var(--ui-01);box-shadow:0 2px 6px 0 rgb(152 162 179 / .25),0 10px 20px 0 rgb(152 162 179 / .1)}.button-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item.active p{color:#fff}.button-tabs.has-icons .snowflake-navigation-container .snowflake-tabs-navigation-item p::before{content:\"\";display:inline-block;width:20px;height:20px;background-size:contain;background-repeat:no-repeat;background-position:center center;margin-right:12px;vertical-align:middle;margin-top:-3px}.logo-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item{width:220px;padding-bottom:50%;height:0;margin:0 8px!important;background-size:cover;background-repeat:no-repeat;opacity:.5;transition:opacity .3s}.logo-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item:hover{opacity:.75;transition:opacity .3s}.logo-tabs .snowflake-navigation-container .snowflake-tabs-navigation-item.active{opacity:1;transition:opacity .3s}.dot-tabs .aem-container.cmp-tabs,.logo-tabs .aem-container.cmp-tabs{display:flex;flex-direction:column-reverse}.snowflake-icon.is-center{margin:0 auto;display:block}#industryPartnerSlider .snowflake-flexible-column-container-items,#partnerLogoSquare .snowflake-flexible-column-container-items{gap:24px}#techResourceOuter::after{content:\"\";display:block;position:absolute;top:0;left:0;width:100%;height:40%;background:#f6f9fa}#techResourceInner{z-index:1}.partner-tier-tag h6{display:inline-block!important;padding:2px 6px;border-radius:2px;color:#666}.partner-tier-tag.registered h6{background-color:#f6f9fa}.partner-tier-tag.elite h6{background-color:#11567f;color:#fff}.partner-tier-tag.premier h6{background-color:#b14c77;color:#fff}.partner-tier-tag.select h6{background-color:#5094a0;color:#fff}.partner-details\u003Espan{display:flex;gap:24px}.partner-details a{color:inherit!important;font-weight:400!important}.partner-details p::before{content:\"\";display:inline-block;vertical-align:middle;width:16px;height:16px;background-repeat:no-repeat;background-position:center;transform:translateY(-1px);background-size:auto 90%;margin-right:6px}.partner-details__location::before{background-image:url(\"data:image/svg+xml,%3Csvg width='13' height='18' viewBox='0 0 13 18' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M6.25 17.7531C6.4375 17.7531 6.6 17.6844 6.7375 17.5531C6.875 17.4219 6.95 17.2531 6.95 17.0531C6.95 16.8531 7.075 16.4281 7.3 15.7969C7.5875 15.0281 7.925 14.3156 8.30625 13.6406C8.8 12.7781 9.3125 12.1031 9.85 11.6094C10.75 10.7969 11.4125 9.96563 11.85 9.12188C12.2875 8.27813 12.5063 7.40313 12.5063 6.49063C12.5063 5.36563 12.2187 4.31563 11.6437 3.33438C11.0937 2.40313 10.3438 1.65938 9.4 1.10938C8.43125 .534376 7.375 .246876 6.24375 .246876C5.1125 .246876 4.06875 .534376 3.0875 1.10938C2.15625 1.65938 1.4125 2.40313 .862498 3.33438C.287498 4.31563 0 5.36563 0 6.49063C0 7.47188 .262499 8.42813 .787499 9.35938C1.14375 10.0031 1.65625 10.6656 2.3125 11.3344C2.75625 11.8031 3.24375 12.4781 3.78125 13.3656C4.225 14.0969 4.63125 14.8594 5 15.6656C5.35 16.3844 5.53125 16.8531 5.55625 17.0656C5.55625 17.2594 5.625 17.4156 5.7625 17.5531C5.9 17.6844 6.0625 17.7531 6.25 17.7531ZM6.16875 14.9156C5.775 14.0656 5.325 13.2469 4.825 12.4594C4.275 11.5594 3.7625 10.8719 3.28125 10.3969C2.625 9.71563 2.1375 9.05938 1.825 8.43438C1.5125 7.80313 1.35625 7.16563 1.35625 6.50313C1.35625 5.61563 1.575 4.80313 2.0125 4.05313C2.45 3.30313 3.04375 2.71563 3.7875 2.27813C4.5375 1.84063 5.35 1.62188 6.2375 1.62188C7.125 1.62188 7.9375 1.84063 8.6875 2.27813C9.4375 2.71563 10.0312 3.30313 10.475 4.04688C10.9187 4.80313 11.1375 5.62188 11.1375 6.50313C11.1375 7.90313 10.3937 9.26563 8.9125 10.5969C8.35 11.1094 7.8125 11.7906 7.3 12.6406C6.88125 13.3344 6.50625 14.0969 6.16875 14.9219V14.9156ZM6.26875 8.36563C6.65625 8.36563 7.01875 8.26563 7.35625 8.07188C7.69375 7.87813 7.95625 7.60938 8.14375 7.28438C8.3375 6.95313 8.43125 6.59063 8.43125 6.19688C8.43125 5.80313 8.33125 5.43438 8.1375 5.10313C7.9375 4.76563 7.675 4.50313 7.3375 4.31563C7 4.12813 6.6375 4.02813 6.24375 4.02813C5.85 4.02813 5.4875 4.12813 5.15625 4.32188C4.825 4.52188 4.56875 4.78438 4.375 5.12188C4.18125 5.45938 4.0875 5.82188 4.0875 6.20938C4.0875 6.59688 4.1875 6.95938 4.38125 7.29688C4.58125 7.63438 4.84375 7.89688 5.18125 8.08438C5.51875 8.27813 5.88125 8.37188 6.26875 8.37188V8.36563ZM6.24375 7.50313C5.8875 7.50313 5.575 7.37188 5.31875 7.11563C5.0625 6.85938 4.93125 6.55313 4.93125 6.19063C4.93125 5.82813 5.0625 5.52188 5.31875 5.26563C5.575 5.00938 5.88125 4.87813 6.24375 4.87813C6.60625 4.87813 6.9125 5.00938 7.16875 5.26563C7.425 5.52188 7.55625 5.82813 7.55625 6.19063C7.55625 6.55313 7.425 6.85938 7.16875 7.11563C6.9125 7.37188 6.60625 7.50313 6.24375 7.50313Z' fill='%2329B5E8'/%3E%3C/svg%3E%0A\")}.partner-details__website::before{background-image:url(\"data:image/svg+xml,%3Csvg width='18' height='16' viewBox='0 0 18 16' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M2.61587 2.96889C2.61587 2.75109 2.79633 2.57062 3.01413 2.57062C3.23192 2.57062 3.41238 2.75109 3.41238 2.96889C3.41238 3.18669 3.23192 3.36716 3.01413 3.36716C2.79633 3.36716 2.61587 3.18669 2.61587 2.96889ZM4.21512 2.96889C4.21512 2.75109 4.39558 2.57062 4.61338 2.57062C4.83117 2.57062 5.01163 2.75109 5.01163 2.96889C5.01163 3.18669 4.83117 3.36716 4.61338 3.36716C4.39558 3.36716 4.21512 3.18669 4.21512 2.96889ZM5.81438 2.96889C5.81438 2.75109 5.99484 2.57062 6.21264 2.57062C6.43043 2.57062 6.61089 2.75109 6.61089 2.96889C6.61089 3.18669 6.43043 3.36716 6.21264 3.36716C5.99484 3.36716 5.81438 3.18669 5.81438 2.96889ZM17.2518 .697559H1.19085C.811258 .697559 .506348 1.0025 .506348 1.38209V14.6179C.506348 14.9975 .811258 15.3024 1.19085 15.3024H17.2518C17.6314 15.3024 17.9363 14.9975 17.9363 14.6179V1.38209C17.9363 1.0025 17.6314 .697559 17.2518 .697559ZM16.5673 2.06035V3.90853H1.86914V2.06035H16.5673ZM1.86914 13.9334V4.78593H16.5673V13.9334H1.86914Z' fill='%2329B5E8'/%3E%3C/svg%3E%0A\")}#partnerSidebar{border-radius:4px;background-color:#fff;padding:24px 24px 32px;border-bottom:6px solid #29b5e8}#partnerSidebar h5,.newsletter-disclaimer p{font-size:14px!important}#partnerSidebar ul{margin-top:0;list-style-type:none;padding:0;display:flex;flex-wrap:wrap;gap:8px}#partnerSidebar li{border:1px solid;border-radius:2px;padding:0 4px!important;font-size:11px!important;letter-spacing:.25px;text-transform:uppercase}div.snowflake-partner-hero-card{width:100%;margin:0}.partner-details__logo{max-width:380px;margin:0 auto}@media screen and (max-width:767px){.left-alignment .hp-hero__subheadline{margin-left:auto;margin-right:auto}.left-alignment .hp-hero__headline .snowflake-title-v2-line,.left-alignment .hp-hero__subheadline .snowflake-title-v2-line{text-align:center}.hero--home__inner .snowflake-flexible-column-container-items-top-padding-large{padding-top:var(--spacing-02)}.section--logo-bar\u003E.snowflake-flexible-column-container-items{display:flex;flex-wrap:wrap;flex-direction:row;justify-content:center;gap:8px}.section--logo-bar\u003E.snowflake-flexible-column-container-items\u003Ediv{width:calc(33.33% - 8px)}.partner-sidebar__mobile-expand{display:inline-block;color:#249edc;border-color:#249edc!important}#partnerSidebar li:nth-child(n+6),.summit-nav__links .snowflake-button-tertiary{display:none}.sc-body__sidebar{background-color:#f6f9fa;padding:24px}.sc-body__content{padding:0 24px 24px}.summit-speaker-card .snowflake-card-v2-advanced-content{padding:24px}}#partnerResources h6,.snowflake-tabs-navigation-item p.body-1{font-size:16px!important}#partnerResources .section--resource-hub{padding:0 16px}#partnerResources .section--resource-hub a,.bwalignl{text-align:left}@media screen and (max-width:1023px){.hero--workload .snowflake-hero-system-media-container{width:100%}}.section--timely-content .snowflake-content-chip,.snowflake-mega-nav-dropdown-footer-wrapper{align-items:center}.section--timely-content .snowflake-content-chip-image{max-width:94px}.section--timely-content .snowflake-content-chip-image__inner{line-height:0}.section--timely-content .snowflake-content-chip-image__image{aspect-ratio:1;height:auto}.section--workload-overview .workload-overview__headline{max-width:280px;margin:0 auto}#industryPartnerSlider .swiper-slide{margin-top:0!important;padding:0 12px}#industryPartnerSlider .snowflake-tabs-navigation-item{margin-left:0!important;margin-right:0!important}#industryPartnerSlider .snowflake-premium-content-banner-background-grad-white .snowflake-premium-content-banner{box-shadow:none}#industryPartnerSlider .logo-slider__slide .aem-container{display:flex;padding:0 8px!important;flex-wrap:wrap;gap:16px!important;justify-content:center}#industryPartnerSlider .logo-slider__slide .aem-container\u003Ediv{width:48%;max-width:200px}#useCaseTabs{padding-top:24px;padding-bottom:24px;padding-right:24px}#useCaseTabs .tab-content.is-active{display:block}#useCaseTabs .vert-tab{border-bottom:1px solid #a0bbcc;padding-bottom:16px}#useCaseTabs .vert-tab p{display:inline-block}#useCaseTabs .vert-tab p:hover{cursor:pointer}#useCaseTabs .vert-tab p,#useCaseTabs .vert-tab.is-active p.not-active{color:#249edc}#useCaseTabs .vert-tab p.is-active,#useCaseTabs .vert-tab.is-active p{color:#000}#industryPlatformSection{background-image:url(/adobe/dynamicmedia/deliver/dm-aid--db074ad5-7122-4c51-87a3-76c3aa466182/double-arrow-bg%403x.png);background-repeat:no-repeat}.snowflake-text p.featured-quote__source{font-weight:900!important;text-transform:uppercase;font-size:16px!important;margin-top:2rem!important}.snowflake-text p.featured-quote__title{margin-top:0!important;font-size:16px!important}.snowflake-case-study-card-logo img{width:auto!important;height:100px!important;transform:translateX(-15%)}.snowflake-quote-item-quote-text{font-weight:600!important}#customerStoryStatsInner\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-direction:row}#customerStoryStat1,#customerStoryStat2{max-width:240px}#storyHighlights{border-radius:4px;padding:1rem}.sc-overview__webinar-promo-banner .snowflake-content-chip-content .snowflake-title-v2-line,.summit-pricing-block__tile .black-blue-text-color .snowflake-title-v2-line{color:#000!important}.snowflake-youtube-embedded-wrapper{border-radius:var(--small-border-radius)}#arcticNavItem::before,#offset::before,#open-source::before{color:var(--text-05);font-family:Texta,sans-serif!important}#offset,.sc-architecture-caption{margin-top:16px}.hero--press .snowflake-title-v2-line{text-transform:none!important}@media screen and (min-width:768px){.subpage-timely-content__inner\u003E.snowflake-flexible-column-container-items{box-shadow:0 10px 20px 0 rgb(152 162 179 / .1),0 2px 6px 0 rgb(152 162 179 / .25);padding:var(--spacing-04);border-radius:4px;overflow:hidden}#partnerLogoSquare{padding:0 0 0 48px}.hero--workload .snowflake-container{max-width:1440px;margin:0 auto!important;align-items:center}#industryPartnerSlider.snowflake-flexible-column-container-2-column-40-60\u003E.snowflake-flexible-column-container-items{grid-template-columns:minmax(40%,4fr) minmax(0,6fr)}#industryPartnerSlider .swiper-slide{padding:0 24px}.sc-body{padding:48px}.sc-body\u003E.snowflake-flexible-column-container-items{grid-template-columns:7fr 3fr;gap:124px}}.snowflake-button-container.has-icon{display:inline-flex;justify-content:center;align-items:center;text-align:left}.snowflake-button-container.has-icon::before{content:\"\";display:inline-block;width:20px;height:20px;margin-right:12px;background-size:contain;background-repeat:no-repeat;background-position:center}.snowflake-button-container.is-video::before{background-image:url(\"data:image/svg+xml,%3Csvg width='18' height='18' viewBox='0 0 18 18' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M9 1.28663C13.2523 1.28663 16.7134 4.74768 16.7134 9C16.7134 13.2523 13.2523 16.7134 9 16.7134C4.74768 16.7198 1.28663 13.2588 1.28663 9C1.28663 4.74124 4.74768 1.28663 9 1.28663ZM9 0C4.0336 0 0 4.0336 0 9C0 13.9664 4.0336 18 9 18C13.9728 18 18 13.9664 18 9C18 4.0336 13.9728 0 9 0Z' fill='white'/%3E%3Cpath d='M7.75106 6.18211C7.42941 6.16925 7.16565 6.42658 7.16565 6.74823V11.2772C7.16565 11.7082 7.65457 11.9848 8.02126 11.7597L11.7975 9.4952C12.1578 9.27647 12.1578 8.74252 11.7975 8.52379L8.02126 6.25931C7.93763 6.21428 7.84756 6.18211 7.75106 6.18211Z' fill='white'/%3E%3C/svg%3E%0A\")}.snowflake-button-container.is-github::before{background-image:url(\"data:image/svg+xml,%3Csvg width='20' height='21' viewBox='0 0 20 21' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 .651794C4.475 .651794 0 5.12679 0 10.6518C0 15.0768 2.8625 18.8143 6.8375 20.1393C7.3375 20.2268 7.525 19.9268 7.525 19.6643C7.525 19.4268 7.5125 18.6393 7.5125 17.8018C5 18.2643 4.35 17.1893 4.15 16.6268C4.0375 16.3393 3.55 15.4518 3.125 15.2143C2.775 15.0268 2.275 14.5643 3.1125 14.5518C3.9 14.5393 4.4625 15.2768 4.65 15.5768C5.55 17.0893 6.9875 16.6643 7.5625 16.4018C7.65 15.7518 7.9125 15.3143 8.2 15.0643C5.975 14.8143 3.65 13.9518 3.65 10.1268C3.65 9.03929 4.0375 8.13929 4.675 7.43929C4.575 7.18929 4.225 6.16429 4.775 4.78929C4.775 4.78929 5.6125 4.52679 7.525 5.81429C8.325 5.58929 9.175 5.47679 10.025 5.47679C10.875 5.47679 11.725 5.58929 12.525 5.81429C14.4375 4.51429 15.275 4.78929 15.275 4.78929C15.825 6.16429 15.475 7.18929 15.375 7.43929C16.0125 8.13929 16.4 9.02679 16.4 10.1268C16.4 13.9643 14.0625 14.8143 11.8375 15.0643C12.2 15.3768 12.5125 15.9768 12.5125 16.9143C12.5125 18.2518 12.5 19.3268 12.5 19.6643C12.5 19.9268 12.6875 20.2393 13.1875 20.1393C17.1375 18.8143 20 15.0643 20 10.6518C20 5.12679 15.525 .651794 10 .651794Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\")}.snowflake-button-container.is-quickstart::before{background-image:url(\"data:image/svg+xml,%3Csvg width='15' height='21' viewBox='0 0 15 21' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M13.8489 2.79368H11.6439V2.38493C11.6439 1.71368 11.1451 .967427 10.4251 .967427H8.94762C8.80887 .359927 8.37387 .299927 7.89762 .299927H7.23012C6.85512 .299927 6.26637 .299927 6.08637 .967427H4.68387C3.94887 .967427 3.35637 1.74368 3.35637 2.38493V2.79368H1.15137C.738867 2.79368 .401367 3.13118 .401367 3.54368V20.2537C.401367 20.6662 .738867 21.0037 1.15137 21.0037H13.8489C14.2614 21.0037 14.5989 20.6662 14.5989 20.2537V3.54368C14.5989 3.13118 14.2614 2.79368 13.8489 2.79368ZM4.29387 2.38493C4.29387 2.18243 4.54137 1.90493 4.68387 1.90493H6.50262C6.76137 1.90493 6.97137 1.69493 6.97137 1.43618C6.97137 1.33868 6.97887 1.27868 6.98637 1.24118C7.05012 1.23368 7.15512 1.23368 7.23387 1.23368H7.90137C7.95012 1.23368 8.00637 1.23368 8.05137 1.23368C8.05512 1.27868 8.05887 1.34243 8.05887 1.43243C8.05887 1.69118 8.26887 1.90118 8.52762 1.90118H10.4289C10.5301 1.90118 10.7101 2.14493 10.7101 2.38118V2.78993H4.29762V2.38118L4.29387 2.38493ZM13.0989 19.4999H1.90137V4.29368H13.0989V19.5037V19.4999Z' fill='%23249EDC'/%3E%3Cpath d='M3.82512 16.0424H11.1751C11.4339 16.0424 11.6439 15.8324 11.6439 15.5736V6.88486C11.6439 6.62611 11.4339 6.41611 11.1751 6.41611H3.82512C3.56637 6.41611 3.35637 6.62611 3.35637 6.88486V15.5736C3.35637 15.8324 3.56637 16.0424 3.82512 16.0424ZM4.29387 15.1049V13.3686H10.7064V15.1049H4.29387ZM10.7101 7.35361V12.4311H4.29762V7.35361H10.7101Z' fill='%23249EDC'/%3E%3Cpath d='M6.16512 9.35989H8.83887C9.09762 9.35989 9.30762 9.14989 9.30762 8.89114C9.30762 8.63239 9.09762 8.42239 8.83887 8.42239H6.16512C5.90637 8.42239 5.69637 8.63239 5.69637 8.89114C5.69637 9.14989 5.90637 9.35989 6.16512 9.35989Z' fill='%23249EDC'/%3E%3Cpath d='M6.16512 11.3624H8.83887C9.09762 11.3624 9.30762 11.1524 9.30762 10.8937C9.30762 10.6349 9.09762 10.4249 8.83887 10.4249H6.16512C5.90637 10.4249 5.69637 10.6349 5.69637 10.8937C5.69637 11.1524 5.90637 11.3624 6.16512 11.3624Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\")}.snowflake-button-container.is-download::before{background-image:url(\"data:image/svg+xml,%3Csvg width='16' height='18' viewBox='0 0 16 18' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M15.2017 17.1637H.798265C.364425 17.1637 0 16.7993 0 16.3655V12.3568C0 11.923 .364425 11.5585 .798265 11.5585C1.2321 11.5585 1.59653 11.923 1.59653 12.3568V15.5498H14.4035V12.3568C14.4035 11.923 14.7679 11.5585 15.2017 11.5585C15.6356 11.5585 16 11.923 16 12.3568V16.3655C16 16.7993 15.6529 17.1637 15.2017 17.1637Z' fill='%23249EDC'/%3E%3Cpath d='M7.94793 12.9642C7.84381 12.9642 7.73969 12.9468 7.63557 12.8947C7.34056 12.7733 7.14967 12.4783 7.14967 12.1485L7.18437 .938127C7.18437 .504287 7.5488 .139862 7.98264 .139862C8.41648 .139862 8.7809 .504287 8.7809 .938127L8.7462 10.257L12.8416 6.33509C13.154 6.02273 13.6746 6.04008 13.9696 6.35244C14.282 6.66481 14.2646 7.18542 13.9523 7.48043L8.50325 12.7386C8.36442 12.8774 8.15617 12.9642 7.94793 12.9642Z' fill='%23249EDC'/%3E%3Cpath d='M7.94793 12.9642C7.73969 12.9642 7.54881 12.8947 7.39262 12.7386L2.03037 7.53249C1.718 7.22012 1.70065 6.71687 2.01301 6.40451C2.32538 6.09214 2.82863 6.07479 3.141 6.38715L8.50325 11.5932C8.81562 11.9056 8.83297 12.4088 8.52061 12.7212C8.36442 12.8774 8.15617 12.9642 7.94793 12.9642Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\")}.snowflake-button-container.is-expand::before{background-image:url(\"data:image/svg+xml,%3Csvg width='18' height='18' viewBox='0 0 18 18' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M6.64375 10.9125C6.9375 11.2062 6.93125 11.6812 6.64375 11.9687L2.57502 16H3.79375C4.20625 16 4.54376 16.3375 4.54376 16.75C4.54376 17.1625 4.20625 17.5 3.79375 17.5H.756264C.556264 17.5 .36876 17.4187 .22501 17.2812C.22501 17.2812 .206248 17.25 .193748 17.2375C.143748 17.1812 .100004 17.1125 .0625038 17.0437C.0375038 16.9687 .0187492 16.8937 .0187492 16.8187C.0187492 16.8 .0062561 16.7813 .0062561 16.7625V13.725C.0187561 13.3125 .356257 12.9875 .768757 12.9937C1.16876 13 1.48752 13.325 1.50002 13.725V14.9688L5.5875 10.9187C5.88125 10.6312 6.35 10.6312 6.64375 10.9187V10.9125ZM17.5063 .743732C17.5063 .543732 17.425 .356235 17.2875 .218735C17.2875 .218735 17.2562 .199998 17.2437 .193748C17.1875 .137498 17.1188 .0937347 17.0438 .0624847C16.9688 .0374847 16.8938 .0187492 16.8188 .0187492C16.8 .0187492 16.7813 .00623703 16.7625 .00623703H13.725C13.3125 .00623703 12.975 .343745 12.975 .756245C12.975 1.16874 13.3125 1.50623 13.725 1.50623H14.9688L11.1312 5.37498C10.8437 5.67498 10.8563 6.14999 11.1563 6.43124C11.45 6.71249 11.9063 6.70624 12.1938 6.43124L16.0125 2.575V3.79375C16.0125 4.20625 16.35 4.54372 16.7625 4.54372C17.175 4.54372 17.5125 4.20625 17.5125 3.79375V.756245L17.5063 .743732ZM16.7562 12.9688C16.3437 12.9688 16.0063 13.3063 16.0063 13.7188V14.8937L12.1938 10.925C11.9063 10.625 11.4375 10.6188 11.1375 10.9063C10.8375 11.1938 10.8313 11.6625 11.1188 11.9625L15 16.0062H13.7188C13.3063 16.0062 12.9688 16.3437 12.9688 16.7562C12.9688 17.1687 13.3063 17.5063 13.7188 17.5063H16.7562C16.85 17.5063 16.95 17.4875 17.0375 17.45C17.0875 17.425 17.1313 17.3937 17.175 17.3625C17.2063 17.3437 17.2438 17.325 17.275 17.3C17.3313 17.2375 17.375 17.1687 17.4125 17.1C17.4188 17.0875 17.4375 17.075 17.4438 17.0562C17.45 17.025 17.4563 16.9938 17.4625 16.9625C17.4813 16.9 17.5 16.8375 17.5 16.7687V13.725C17.5 13.3125 17.1687 12.975 16.7562 12.975V12.9688ZM.750008 4.53125C1.16251 4.53125 1.50002 4.19374 1.50002 3.78124V2.5L5.59376 6.43124C5.89376 6.71874 6.36251 6.70626 6.65001 6.41251C6.93751 6.11876 6.92501 5.64375 6.63126 5.35625L2.61251 1.49998H3.7875C4.2 1.49998 4.53751 1.16249 4.53751 .749989C4.53751 .337489 4.2 0 3.7875 0H.743752C.668752 0 .600004 .0187355 .531254 .0437355C.506254 .0499855 .481263 .0437477 .462513 .0562477C.443763 .0687477 .425015 .0812462 .406265 .0937462C.337515 .124996 .275004 .168741 .218754 .224991H.212498C.212498 .224991 .175 .28125 .15625 .3125C.11875 .3625 .0812477 .4125 .0562477 .46875C.0374977 .525 .0249992 .587499 .0187492 .643749C.0124992 .674999 0 .712482 0 .743732V3.78124C0 4.19374 .337508 4.53125 .750008 4.53125Z' fill='white'/%3E%3C/svg%3E%0A\")}@keyframes slow-scroll{100%{transform:translateY(-50%)}}.sc-hero{overflow:hidden;background-color:#212d35;background-repeat:repeat-y;background-image:url(\"data:image/svg+xml,%3Csvg width='389' height='17' viewBox='0 0 389 17' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M.638672 7.80824L.638672 9.2566C.638672 9.52364 .85538 9.74024 1.12262 9.74024H2.57204C2.83928 9.74024 3.05598 9.52364 3.05598 9.2566V7.80824C3.05598 7.54119 2.83928 7.32472 2.57204 7.32472L1.12262 7.32472C.85538 7.32472 .638672 7.54119 .638672 7.80824Z' fill='url(%23paint0_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10.9639 7.80824V9.2566C10.9639 9.52364 11.1806 9.74024 11.4478 9.74024L12.8972 9.74024C13.1645 9.74024 13.3812 9.52364 13.3812 9.2566V7.80824C13.3812 7.54119 13.1645 7.32471 12.8972 7.32471L11.4478 7.32471C11.1806 7.32471 10.9639 7.54119 10.9639 7.80824Z' fill='url(%23paint1_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M21.2891 7.80823V9.2566C21.2891 9.52364 21.5058 9.74024 21.773 9.74024L23.2224 9.74024C23.4897 9.74024 23.7064 9.52364 23.7064 9.2566V7.80823C23.7064 7.54119 23.4897 7.32471 23.2224 7.32471L21.773 7.32471C21.5058 7.32471 21.2891 7.54119 21.2891 7.80823Z' fill='url(%23paint2_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M31.6143 7.80823V9.2566C31.6143 9.52364 31.831 9.74024 32.0982 9.74024H33.5476C33.8149 9.74024 34.0316 9.52364 34.0316 9.2566V7.80823C34.0316 7.54119 33.8149 7.32471 33.5476 7.32471L32.0982 7.32471C31.831 7.32471 31.6143 7.54119 31.6143 7.80823Z' fill='url(%23paint3_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M41.9395 7.80823V9.2566C41.9395 9.52364 42.1562 9.74024 42.4234 9.74024H43.8728C44.1401 9.74024 44.3568 9.52364 44.3568 9.2566V7.80823C44.3568 7.54119 44.1401 7.32471 43.8728 7.32471L42.4234 7.32471C42.1562 7.32471 41.9395 7.54119 41.9395 7.80823Z' fill='url(%23paint4_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M52.5076 7.80823V9.2566C52.5076 9.52364 52.7243 9.74024 52.9916 9.74024H54.441C54.7082 9.74024 54.9249 9.52364 54.9249 9.2566V7.80823C54.9249 7.54119 54.7082 7.32471 54.441 7.32471L52.9916 7.32471C52.7243 7.32471 52.5076 7.54119 52.5076 7.80823Z' fill='url(%23paint5_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M62.8331 7.80823V9.2566C62.8331 9.52364 63.0493 9.74024 63.3165 9.74024H64.7664C65.0332 9.74024 65.2504 9.52364 65.2504 9.2566V7.80823C65.2504 7.54119 65.0332 7.32471 64.7664 7.32471L63.3165 7.32471C63.0493 7.32471 62.8331 7.54119 62.8331 7.80823Z' fill='url(%23paint6_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M73.1583 7.80823V9.2566C73.1583 9.52364 73.3745 9.74024 73.6417 9.74024H75.0916C75.3584 9.74024 75.5756 9.52364 75.5756 9.2566V7.80823C75.5756 7.54119 75.3584 7.32471 75.0916 7.32471L73.6417 7.32471C73.3745 7.32471 73.1583 7.54119 73.1583 7.80823Z' fill='url(%23paint7_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M83.4835 7.80823V9.2566C83.4835 9.52364 83.6997 9.74024 83.9669 9.74024H85.4168C85.6836 9.74024 85.9008 9.52364 85.9008 9.2566V7.80823C85.9008 7.54119 85.6836 7.32471 85.4168 7.32471L83.9669 7.32471C83.6997 7.32471 83.4835 7.54119 83.4835 7.80823Z' fill='url(%23paint8_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M93.8087 7.80823V9.2566C93.8087 9.52364 94.0249 9.74024 94.2921 9.74024H95.742C96.0088 9.74024 96.226 9.52364 96.226 9.2566V7.80823C96.226 7.54119 96.0088 7.32471 95.742 7.32471L94.2921 7.32471C94.0249 7.32471 93.8087 7.54119 93.8087 7.80823Z' fill='url(%23paint9_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M104.134 7.80823V9.2566C104.134 9.52364 104.35 9.74024 104.617 9.74024H106.067C106.334 9.74024 106.551 9.52364 106.551 9.2566V7.80823C106.551 7.54119 106.334 7.32471 106.067 7.32471L104.617 7.32471C104.35 7.32471 104.134 7.54119 104.134 7.80823Z' fill='url(%23paint10_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M114.702 7.80823V9.2566C114.702 9.52364 114.918 9.74024 115.185 9.74024L116.635 9.74024C116.902 9.74024 117.119 9.52364 117.119 9.25659V7.80823C117.119 7.54119 116.902 7.32471 116.635 7.32471L115.185 7.32471C114.918 7.32471 114.702 7.54119 114.702 7.80823Z' fill='url(%23paint11_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M125.027 7.80823V9.25659C125.027 9.52364 125.243 9.74024 125.511 9.74024L126.961 9.74024C127.227 9.74024 127.445 9.52364 127.445 9.25659V7.80823C127.445 7.54119 127.227 7.32471 126.961 7.32471L125.511 7.32471C125.243 7.32471 125.027 7.54119 125.027 7.80823Z' fill='url(%23paint12_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M135.352 7.80823V9.25659C135.352 9.52364 135.569 9.74024 135.836 9.74024H137.286C137.553 9.74024 137.77 9.52364 137.77 9.25659V7.80823C137.77 7.54119 137.553 7.32471 137.286 7.32471L135.836 7.32471C135.569 7.32471 135.352 7.54119 135.352 7.80823Z' fill='url(%23paint13_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M145.678 7.80823V9.25659C145.678 9.52364 145.894 9.74024 146.161 9.74024H147.611C147.878 9.74024 148.095 9.52364 148.095 9.25659V7.80823C148.095 7.54119 147.878 7.32471 147.611 7.32471L146.161 7.32471C145.894 7.32471 145.678 7.54119 145.678 7.80823Z' fill='url(%23paint14_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M156.003 7.80823V9.25659C156.003 9.52364 156.219 9.74024 156.486 9.74024H157.936C158.203 9.74024 158.42 9.52364 158.42 9.25659V7.80823C158.42 7.54119 158.203 7.32471 157.936 7.32471L156.486 7.32471C156.219 7.32471 156.003 7.54119 156.003 7.80823Z' fill='url(%23paint15_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M166.328 7.80823V9.25659C166.328 9.52363 166.544 9.74024 166.811 9.74024H168.261C168.528 9.74024 168.745 9.52363 168.745 9.25659V7.80823C168.745 7.54119 168.528 7.32471 168.261 7.32471L166.811 7.32471C166.544 7.32471 166.328 7.54119 166.328 7.80823Z' fill='url(%23paint16_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M176.896 7.80823V9.25659C176.896 9.52363 177.112 9.74023 177.38 9.74023H178.83C179.096 9.74023 179.313 9.52363 179.313 9.25659V7.80823C179.313 7.54119 179.096 7.32471 178.83 7.32471L177.38 7.32471C177.112 7.32471 176.896 7.54119 176.896 7.80823Z' fill='url(%23paint17_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M187.221 7.80823V9.25659C187.221 9.52363 187.438 9.74023 187.705 9.74023H189.155C189.421 9.74023 189.639 9.52363 189.639 9.25659V7.80823C189.639 7.54119 189.421 7.32471 189.155 7.32471L187.705 7.32471C187.438 7.32471 187.221 7.54119 187.221 7.80823Z' fill='url(%23paint18_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M199.639 7.80824V9.2566C199.639 9.52364 199.855 9.74024 200.123 9.74024H201.572C201.839 9.74024 202.056 9.52364 202.056 9.2566V7.80824C202.056 7.54119 201.839 7.32472 201.572 7.32472L200.123 7.32472C199.855 7.32472 199.639 7.54119 199.639 7.80824Z' fill='url(%23paint19_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M209.964 7.80824V9.2566C209.964 9.52364 210.181 9.74024 210.448 9.74024L211.897 9.74024C212.164 9.74024 212.381 9.52364 212.381 9.2566V7.80824C212.381 7.54119 212.164 7.32471 211.897 7.32471L210.448 7.32471C210.181 7.32471 209.964 7.54119 209.964 7.80824Z' fill='url(%23paint20_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M220.289 7.80823V9.2566C220.289 9.52364 220.506 9.74024 220.773 9.74024L222.222 9.74024C222.49 9.74024 222.706 9.52364 222.706 9.2566V7.80823C222.706 7.54119 222.49 7.32471 222.222 7.32471L220.773 7.32471C220.506 7.32471 220.289 7.54119 220.289 7.80823Z' fill='url(%23paint21_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M230.614 7.80823V9.2566C230.614 9.52364 230.831 9.74024 231.098 9.74024H232.548C232.815 9.74024 233.032 9.52364 233.032 9.2566V7.80823C233.032 7.54119 232.815 7.32471 232.548 7.32471L231.098 7.32471C230.831 7.32471 230.614 7.54119 230.614 7.80823Z' fill='url(%23paint22_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M240.939 7.80823V9.2566C240.939 9.52364 241.156 9.74024 241.423 9.74024H242.873C243.14 9.74024 243.357 9.52364 243.357 9.2566V7.80823C243.357 7.54119 243.14 7.32471 242.873 7.32471L241.423 7.32471C241.156 7.32471 240.939 7.54119 240.939 7.80823Z' fill='url(%23paint23_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M251.508 7.80823V9.2566C251.508 9.52364 251.724 9.74024 251.992 9.74024H253.441C253.708 9.74024 253.925 9.52364 253.925 9.2566V7.80823C253.925 7.54119 253.708 7.32471 253.441 7.32471L251.992 7.32471C251.724 7.32471 251.508 7.54119 251.508 7.80823Z' fill='url(%23paint24_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M261.833 7.80823V9.2566C261.833 9.52364 262.049 9.74024 262.317 9.74024H263.766C264.033 9.74024 264.25 9.52364 264.25 9.2566V7.80823C264.25 7.54119 264.033 7.32471 263.766 7.32471L262.317 7.32471C262.049 7.32471 261.833 7.54119 261.833 7.80823Z' fill='url(%23paint25_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M272.158 7.80823V9.2566C272.158 9.52364 272.374 9.74024 272.642 9.74024H274.092C274.358 9.74024 274.576 9.52364 274.576 9.2566L274.576 7.80823C274.576 7.54119 274.358 7.32471 274.092 7.32471L272.642 7.32471C272.374 7.32471 272.158 7.54119 272.158 7.80823Z' fill='url(%23paint26_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M282.483 7.80823V9.2566C282.483 9.52364 282.7 9.74024 282.967 9.74024H284.417C284.684 9.74024 284.901 9.52364 284.901 9.2566V7.80823C284.901 7.54119 284.684 7.32471 284.417 7.32471L282.967 7.32471C282.7 7.32471 282.483 7.54119 282.483 7.80823Z' fill='url(%23paint27_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M292.809 7.80823L292.809 9.2566C292.809 9.52364 293.025 9.74024 293.292 9.74024H294.742C295.009 9.74024 295.226 9.52364 295.226 9.2566V7.80823C295.226 7.54119 295.009 7.32471 294.742 7.32471L293.292 7.32471C293.025 7.32471 292.809 7.54119 292.809 7.80823Z' fill='url(%23paint28_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M303.134 7.80823L303.134 9.2566C303.134 9.52364 303.35 9.74024 303.617 9.74024H305.067C305.334 9.74024 305.551 9.52364 305.551 9.2566V7.80823C305.551 7.54119 305.334 7.32471 305.067 7.32471L303.617 7.32471C303.35 7.32471 303.134 7.54119 303.134 7.80823Z' fill='url(%23paint29_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M313.702 7.80823L313.702 9.2566C313.702 9.52364 313.918 9.74024 314.185 9.74024L315.635 9.74024C315.902 9.74024 316.119 9.52364 316.119 9.25659V7.80823C316.119 7.54119 315.902 7.32471 315.635 7.32471L314.185 7.32471C313.918 7.32471 313.702 7.54119 313.702 7.80823Z' fill='url(%23paint30_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M324.027 7.80823V9.25659C324.027 9.52364 324.243 9.74024 324.511 9.74024L325.961 9.74024C326.227 9.74024 326.445 9.52364 326.445 9.25659V7.80823C326.445 7.54119 326.227 7.32471 325.961 7.32471L324.511 7.32471C324.243 7.32471 324.027 7.54119 324.027 7.80823Z' fill='url(%23paint31_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M334.352 7.80823V9.25659C334.352 9.52364 334.569 9.74024 334.836 9.74024H336.286C336.553 9.74024 336.77 9.52364 336.77 9.25659L336.77 7.80823C336.77 7.54119 336.553 7.32471 336.286 7.32471L334.836 7.32471C334.569 7.32471 334.352 7.54119 334.352 7.80823Z' fill='url(%23paint32_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M344.678 7.80823V9.25659C344.678 9.52364 344.894 9.74024 345.161 9.74024H346.611C346.878 9.74024 347.095 9.52364 347.095 9.25659L347.095 7.80823C347.095 7.54119 346.878 7.32471 346.611 7.32471L345.161 7.32471C344.894 7.32471 344.678 7.54119 344.678 7.80823Z' fill='url(%23paint33_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M355.003 7.80823V9.25659C355.003 9.52364 355.219 9.74024 355.486 9.74024H356.936C357.203 9.74024 357.42 9.52364 357.42 9.25659L357.42 7.80823C357.42 7.54119 357.203 7.32471 356.936 7.32471L355.486 7.32471C355.219 7.32471 355.003 7.54119 355.003 7.80823Z' fill='url(%23paint34_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M365.328 7.80823V9.25659C365.328 9.52363 365.544 9.74024 365.811 9.74024H367.261C367.528 9.74024 367.745 9.52363 367.745 9.25659V7.80823C367.745 7.54119 367.528 7.32471 367.261 7.32471L365.811 7.32471C365.544 7.32471 365.328 7.54119 365.328 7.80823Z' fill='url(%23paint35_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M375.896 7.80823V9.25659C375.896 9.52363 376.112 9.74023 376.38 9.74023H377.83C378.096 9.74023 378.313 9.52363 378.313 9.25659V7.80823C378.313 7.54119 378.096 7.32471 377.829 7.32471L376.38 7.32471C376.112 7.32471 375.896 7.54119 375.896 7.80823Z' fill='url(%23paint36_linear_8295_70635)'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M386.221 7.80823V9.25659C386.221 9.52363 386.438 9.74023 386.705 9.74023H388.155C388.421 9.74023 388.639 9.52363 388.639 9.25659V7.80823C388.639 7.54119 388.421 7.32471 388.155 7.32471L386.705 7.32471C386.438 7.32471 386.221 7.54119 386.221 7.80823Z' fill='url(%23paint37_linear_8295_70635)'/%3E%3Cdefs%3E%3ClinearGradient id='paint0_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint1_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint2_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint3_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint4_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint5_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint6_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint7_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint8_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint9_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint10_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint11_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint12_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint13_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint14_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint15_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint16_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint17_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint18_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint19_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint20_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint21_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint22_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint23_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint24_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint25_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint26_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint27_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint28_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint29_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint30_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint31_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint32_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint33_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint34_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint35_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint36_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3ClinearGradient id='paint37_linear_8295_70635' x1='-47.5' y1='8.99989' x2='332' y2='8.99989' gradientUnits='userSpaceOnUse'%3E%3Cstop stop-color='%2329B5E8' stop-opacity='.8'/%3E%3Cstop offset='1' stop-color='%2329B5E8' stop-opacity='0'/%3E%3C/linearGradient%3E%3C/defs%3E%3C/svg%3E%0A\")}.sc-hero__inner\u003E.snowflake-flexible-column-container-items\u003Ediv:first-child{position:relative;z-index:3}.sc-hero__inner\u003E.snowflake-flexible-column-container-items\u003Ediv:last-child{position:absolute;height:100%;width:100%;top:0;left:-24px}.sc-hero__inner\u003E.snowflake-flexible-column-container-items\u003Ediv:last-child::before{content:\"\";display:block;z-index:1;position:absolute;top:-64px;left:0;width:150%;height:calc(100% + 160px);background-color:rgb(32 44 53 / .9)}.sc-body__content .heading-3-v2,.sc-hero__headline .heading-1-v2{text-transform:none}.sc-body__content span.snowflake-image-caption{display:block!important;font-style:italic}.sc-body__content .snowflake-text p+ul{margin-top:24px!important;padding-left:16px!important}.white-blue-text-color .snowflake-title-v2.solution-center-hero__certification .snowflake-typographyv2\u003Espan.snowflake-title-v2-line{color:#e9eaeb!important;font-size:16px}.white-blue-text-color .snowflake-title-v2.solution-center-hero__certification.is-large .snowflake-typographyv2\u003Espan.snowflake-title-v2-line{color:#fff!important;font-size:18px}.solution-center-hero__certification\u003E.snowflake-title-v2-line\u003Espan:first-child{display:flex;justify-content:flex-start;align-items:center;gap:8px}.solution-center-hero__certification\u003E.snowflake-title-v2-line\u003Espan:first-child::before{content:\"\";display:inline-block;width:16px;height:16px;background-image:url(\"data:image/svg+xml,%3Csvg width='16' height='16' viewBox='0 0 16 16' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M8 0C3.58146 0 0 3.58146 0 8C0 12.4185 3.58146 16 8 16C12.4185 16 16 12.4185 16 8C16 3.58146 12.4185 0 8 0ZM12.7184 5.91984L7.33471 11.3026C7.31293 11.3244 7.31293 11.3454 7.29198 11.3454L7.20653 11.4308C6.94933 11.688 6.54132 11.7525 6.21962 11.6235C6.11238 11.5808 6.00514 11.5163 5.9197 11.4308L5.83425 11.3454C5.83425 11.3454 5.83425 11.3236 5.81246 11.3236L3.28149 8.79347C2.93799 8.44997 2.93799 7.87107 3.28149 7.50664L3.36694 7.42119C3.71044 7.07769 4.28934 7.07769 4.65377 7.42119L6.58401 9.35143L11.3877 4.5477C11.7312 4.2042 12.3101 4.2042 12.6746 4.5477L12.76 4.63315C13.0826 4.99758 13.0828 5.55541 12.7184 5.91984Z' fill='%230E8A16'/%3E%3C/svg%3E%0A\");background-size:contain;background-repeat:no-repeat;background-color:#fff;border-radius:100%}.sc-hero__byline{padding-top:8px}.sc-hero__byline p{color:#e2e2e2;margin-top:0!important}.sc-hero pre[class*=language-]{overflow:visible}.snowflake-code-snippet,.snowflake-code-snippet code,.snowflake-code-snippet pre{font-size:16px}.sc-hero__code-snippet:not(pre)\u003Ecode[class*=language-],.sc-hero__code-snippet pre[class*=language-]{background:0 0}.sc-hero__code-snippet{opacity:.8;background-color:transparent!important;position:absolute;top:0;right:0;width:100%;animation:240s linear 1s forwards slow-scroll}.sc-hero__button-container .snowflake-flexible-column-container-items{padding:0 0 24px;margin-top:-8px;margin-left:24px}.sc-sidebar__partner-logo{width:100%;max-width:140px;margin-top:8px}.sc-sidebar__partner-logo .cmp-image__image{border-radius:0}.sc-tag-cluster.snowflake-text ul{list-style-type:none;padding:0;display:flex;flex-wrap:wrap;gap:8px;margin:0}.sc-tag-cluster.snowflake-text li{color:#373f41;border-radius:4px;display:inline-block;padding:6px;text-transform:uppercase;letter-spacing:1px;font-size:12px!important;line-height:12px!important;margin:0!important;background-color:#f3f3f3}.sc-body .share-icon svg{height:24px;cursor:pointer}.sc-body .share-icon svg:hover path{fill:var(--ui-02)}.sc-overview__webinar-promo-banner{align-items:center;border:1px solid #ccc;padding:var(--spacing-02)}.sc-overview__webinar-promo-banner .snowflake-content-chip-image{max-width:32px;margin-right:var(--spacing-02);line-height:0}.sc-overview__webinar-promo-banner .snowflake-content-chip-image__image,.summit-speaker-card .snowflake-card-v2-advanced-image__image{aspect-ratio:1}.sc-overview__webinar-promo-banner .snowflake-content-chip-content .heading-5-v2{font-size:14px;font-family:Lato,sans-serif}.sc-overview__webinar-promo-banner .snowflake-content-chip-content .snowflake-title-v2-line:not(:first-child){font-weight:400}.sc-overview__webinar-promo-banner .snowflake-content-chip-button .snowflake-button-container{font-size:14px!important}.diagram-group__button{position:absolute;bottom:24px;right:24px;background-color:#212c35!important}.section--mountains-bottom,.summit-hp-hero{position:relative}.sc-cert-banner{background-color:#212d35;border-radius:8px;padding:24px;overflow:hidden}.sc-cert-banner\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-direction:row;align-items:center}:root{--text-secondary:#706f6f;--summit-bg-ltblue:#eaf8fd;--summit-bg-blue:#249edc;--summit-border:#d2d1d4;--summit-border-radius:8px;--summit-card-padding:32px;--summit-card-padding-sm:28px}.section--mountains-bottom::after,.section--mountains-bottom::before{content:\"\";display:block;position:absolute;bottom:-1px;max-width:400px;background-size:100% auto;height:100%;width:30%;line-height:0;background-repeat:no-repeat}.button-group\u003E.container\u003E.cmp-container\u003E.aem-container{justify-content:center;align-items:center}.button-group\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:auto!important;margin:0 8px!important}.button-group .snowflake-button-container{font-family:Texta,sans-serif}.section--summit-bg-ltblue{background-color:var(--summit-bg-ltblue)}.section--summit-bg-blue,.summit-hero-secondary{background-color:var(--summit-bg-blue)}.section--mountains-bottom::before{left:0;background-image:url(\"data:image/svg+xml,%3Csvg width='402' height='309' viewBox='0 0 402 309' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M401.523 308.761H0V0L181.63 182.431L228.479 135.531L401.523 308.761Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\");background-position:bottom left}.section--mountains-bottom::after{right:0;background-image:url(\"data:image/svg+xml,%3Csvg width='402' height='309' viewBox='0 0 402 309' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 308.761H401.523V0L219.893 182.431L173.044 135.531L0 308.761Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\");background-position:bottom right}.summit-hp-hero{overflow:hidden}.summit-hero__bg-video{position:absolute;top:50%;left:50%;width:120%;height:100%;opacity:.3;transform:translate(-50%,-50%)}.summit-hero__bg-svg,.summit-prefooter__bg-image,.summit-secondary-hero__bg-image{position:absolute;bottom:0;left:0;width:100%}.summit-hp-promo-banner__headline .heading-4-v2{font-weight:900}.summit-hero-secondary .hero-lottie__left{position:absolute;bottom:0;left:0;width:30%;line-height:0}.summit-timeline__card::after,.summit-timeline__card::before{bottom:0;left:50%;position:absolute;display:block;background-color:var(--ui-01);content:\"\"}.summit-hero-secondary .snowflake-text p{font-size:24px!important;line-height:32px!important;max-width:720px;margin:0 auto}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;justify-content:center}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:auto!important;max-width:25%}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:not(:last-child){border-right:1px solid #fff}.summit-timeline__card{border:1px solid var(--summit-border);border-radius:var(--summit-border-radius);padding:var(--summit-card-padding);position:relative;background-color:#fff}.summit-timeline__card::before{width:20px;height:20px;border-radius:100%;transform:translate(-50%,50%)}.summit-timeline__card::after{width:3px;height:50px;transform:translate(-50%,100%)}.summit-timeline-card__icon{width:48px;height:48px}.summit-timeline-card__headline .heading-3-v2{font-size:32px}.faq-group{border:1px solid var(--ui-12);border-radius:4px;background-color:#fff}.faq-group__question{padding:24px}.faq-group__question:hover{color:var(--ui-01);cursor:pointer}.faq-group__question .heading-4-v2,.faq-group__question .heading-5-v2{position:relative;padding-right:64px}.faq-group__question .heading-4-v2::after,.faq-group__question .heading-5-v2::after{content:\"\";display:block;width:32px;height:32px;background-image:url(\"data:image/svg+xml,%3Csvg width='29' height='16' viewBox='0 0 29 16' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M14.16 14.6807C14.2537 14.7957 14.3719 14.8884 14.506 14.952C14.64 15.0157 14.7866 15.0487 14.935 15.0487C15.0834 15.0487 15.2299 15.0157 15.3639 14.952C15.498 14.8884 15.6162 14.7957 15.71 14.6807V14.6807L28.51 2.00068C29.07 1.43068 29.07 .92068 28.51 .44068C27.95 -.0393204 27.43 -.11932 26.96 .44068L14.94 12.0007L2.99996 .45068C2.90725 .322624 2.7855 .218374 2.6447 .146483C2.50389 .0745926 2.34805 .0371094 2.18996 .0371094C2.03187 .0371094 1.87603 .0745926 1.73522 .146483C1.59442 .218374 1.47267 .322624 1.37996 .45068C.819961 .93068 .819961 1.45068 1.37996 2.01068L14.16 14.6807Z' fill='black'/%3E%3C/svg%3E%0A\");background-size:80% auto;background-repeat:no-repeat;background-position:center;position:absolute;top:-2px;right:0;transition:.3s 150ms}.faq-group__question .heading-5-v2::after{top:-4px}.faq-group__answer{max-height:0;overflow:hidden;width:95%;padding:0 24px;transition:.5s}.faq-group__answer\u003Espan{display:block;padding-bottom:24px}.is-open .faq-group__answer{max-height:600px;transition:1s}.is-open .faq-group__question .heading-4-v2::after,.is-open .faq-group__question .heading-5-v2::after{transform:rotate(180deg);transition:.3s}.summit-agenda{box-shadow:2px 4px 10px 0 rgb(156 156 156 / .52);border-radius:8px;background-color:#fff;max-width:980px;margin-left:auto;margin-right:auto;padding:40px;width:90%}.agenda-item{border-radius:8px;background-color:#d4f0fa;padding:16px;border-left:4px solid var(--ui-01);position:relative}.summit-pricing-block__tile.is-past,.summit-pricing-block__tile.is-upcoming{pointer-events:none;border-color:#d2d1d4}p.agenda-item__time{width:25%;font-family:Texta!important;font-size:32px!important;font-weight:900!important;text-transform:uppercase!important;max-width:140px}@media screen and (max-width:991px){#partnerResources .section--resource-hub .snowflake-button-link .snowflake-button-container{font-size:14px!important;line-height:20px!important;margin-top:4px}#industryPartnerSlider\u003E.snowflake-flexible-column-container-items{display:flex;flex-direction:column}#industryPartnerSlider\u003E.snowflake-flexible-column-container-items\u003Ediv{width:100%}.sc-cert-banner__left{text-align:center}.sc-cert-banner__left .solution-center-hero__certification .snowflake-title-v2-line{justify-content:center}.summit-hero__bg-video{width:200%}.summit-leadership-grid .snowflake-flexible-column-container-items{grid-template-columns:repeat(2,1fr)}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:50%!important;max-width:50%!important}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:not(:last-child){border-right:none!important}.summit-agenda{padding:24px}p.agenda-item__time{font-size:24px!important;width:auto;white-space:nowrap;padding-right:24px}}.agenda-item\u003Espan{display:flex;align-items:center}.summit-add-on-block,.summit-pricing-block{border:1px solid #d2d1d4;border-radius:8px;overflow:hidden;box-shadow:2px 4px 10px 0 rgb(156 156 156 / .52);background-color:#fff}.summit-add-on-block__content,.summit-pricing-block__content{padding:0 20px 20px}.summit-pricing-block__tile{padding:24px 20px;border-radius:4px;background:#fff;border:1px solid var(--ui-01);position:relative;transition:background-color .3s}.summit-pricing-block__tile:hover{background-color:var(--ui-01);transition:background-color .3s}.summit-pricing-block__tile.is-past{background-color:#d4f0fa}.summit-pricing-block__tile:hover .black-blue-text-color .snowflake-title-v2-line{color:#fff!important;transition:color .3s}.partner-card__logo-grid\u003E.container\u003E.cmp-container\u003E.aem-container::after,.partner-card__logo-grid\u003E.container\u003E.cmp-container\u003E.aem-container::before,.summit-add-on-block__content\u003E.container\u003E.cmp-container\u003E.aem-container::after,.summit-add-on-block__content\u003E.container\u003E.cmp-container\u003E.aem-container::before,.summit-pricing-block__tile.is-past .snowflake-content-chip-button,.summit-pricing-block__tile.is-upcoming .snowflake-content-chip-button,.summit-speaker-card .snowflake-card-v2-advanced-tag-indicator{display:none}.summit-pricing-block__tile.is-past .black-blue-text-color .snowflake-title-v2-line{color:#7cc7eb!important}.summit-pricing-block__tile.is-upcoming .black-blue-text-color .snowflake-title-v2-line{color:#8c8c8c!important}.summit-pricing-block__aside{background-color:#d4f0fa;border:1px solid #d2d1d4;border-radius:8px;padding:24px;width:100%}.summit-pricing-block__aside li::marker{color:var(--ui-01)}.summit-pricing-block__aside-headline .heading-5-v2{font-weight:900;margin-bottom:12px}.summit-pricing-block__header{background:#000;padding:24px 40px}.summit-pricing-block__header .heading-4-v2{font-weight:900;letter-spacing:.5px}.bwwidth100,.snowflake-mega-nav-dropdown-footer-content,.summit-pricing-block__tile .black-blue-text-color{width:100%}.summit-pricing-block__tile .heading-5-v2{position:static}.summit-pricing-block__tile .heading-5-v2 span.snowflake-title-v2-line:first-child{text-transform:uppercase;font-weight:900!important;letter-spacing:.25px;font-size:24px!important}.summit-pricing-block__tile .heading-5-v2 span.snowflake-title-v2-line:nth-child(2){margin-top:8px;font-family:Lato,sans-serif;font-size:14px;font-style:normal;font-weight:400;line-height:16px}.summit-pricing-block__tile .heading-5-v2 span.snowflake-title-v2-line:last-child{font-weight:900!important;font-size:40px!important}.snowflake-mega-nav-nav-item\u003Ea:hover .snowflake-mega-nav-nav-item-title-wrapper\u003E.snowflake-mega-nav-nav-item-title,.summit-pricing-block__tile:not(.is-upcoming):not(.is-past) .heading-5-v2 span.snowflake-title-v2-line:last-child{color:var(--ui-01)!important}.summit-pricing-block__tile:hover:not(.is-upcoming):not(.is-past) .heading-5-v2 span.snowflake-title-v2-line:last-child{color:#fff!important}.summit-pricing-block__tile.is-past .heading-5-v2 span.snowflake-title-v2-line:last-child{text-decoration:line-through}.summit-pricing-block__tile .snowflake-content-chip-button{margin-top:0;white-space:nowrap;display:none}.snowflake-card-v2-advanced.no-link{pointer-events:none!important}.snowpro-card{border:1px solid var(--summit-border);border-radius:var(--summit-border-radius);padding:var(--summit-card-padding-sm);display:flex;height:100%}.snowpro-card__headline{margin:24px 0 12px}.snowpro-card__pricing{margin-top:48px}.snowpro-card .snowflake-text .snowpro-card__price{color:var(--ui-01);font-weight:900;font-size:40px!important;font-family:Texta,sans-serif}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-direction:row;flex-wrap:wrap}.summit-stat-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:not(:last-child){border-right:1px solid var(--summit-border)}.summit-stat-card{padding:0 40px}.summit-stat .heading-2-v2 .snowflake-title-v2-line:first-child{font-size:64px;line-height:52px;margin-bottom:8px}.summit-stat .heading-2-v2 .snowflake-title-v2-line:last-child{font-size:32px;line-height:30px;margin-bottom:16px}.summit-speaker-card .snowflake-card-v2-advanced-title{margin-bottom:var(--spacing-01)}.summit-add-on-card{padding:24px;border:1px solid #d2d1d4;border-radius:8px}.summit-add-on__subhead{padding-left:40px;padding-right:40px}.partner-card__logo-grid,.partner-card__logo-single{padding:40px}.partner-card__logo-grid .snowflake-image-container .cmp-image__image,.partner-card__logo-single .snowflake-image-container .cmp-image__image{border-radius:0;max-width:240px;margin:0 auto}.partner-card\u003E.container,.partner-card\u003E.container\u003E.aem-container,.partner-card\u003E.container\u003E.cmp-container{height:100%}.summit-add-on-block__content\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-direction:row;gap:24px;align-items:stretch}.partner-card__logo-grid\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-direction:row;flex-wrap:wrap;gap:40px 24px;justify-content:center;align-items:center}.partner-card__logo-grid\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(33.3333% - 24px);margin:0!important}.partner-card{border-radius:8px;border:1px solid #d2d1d4;overflow:hidden;height:100%;background-color:#fff}.partner-card__header{padding:16px 24px;border-bottom:1px solid #d2d1d4}.partner-card__header.is-purple{background-color:#7d44cf}.partner-card__header h4{display:flex;flex-direction:row!important;align-items:center;gap:12px}.partner-card__header h4::before{vertical-align:middle;content:\"\";display:inline-block;width:20px;height:20px;background-size:contain;background-repeat:no-repeat;background-image:url(\"data:image/svg+xml,%3Csvg width='21' height='23' viewBox='0 0 21 23' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M20.0375 12.8374C20.1644 12.439 20.2172 12.0289 20.2077 11.6237C20.193 11.3305 20.1548 11.0373 20.0712 10.7441C19.8196 9.83306 19.223 9.01989 18.3294 8.50724L5.61817 1.2017C3.82388 .173815 1.53618 .784335 .506483 2.56804C-.533615 4.34915 .0797871 6.62351 1.87408 7.65398L8.97715 11.7427L1.87408 15.8201C.0797871 16.8527 -.531016 19.1271 .506483 20.9156C1.53618 22.6941 3.82388 23.302 5.61817 22.2746L18.3294 14.9643C19.1871 14.4728 19.7693 13.7027 20.0375 12.8374Z' fill='black'/%3E%3C/svg%3E%0A\")}.partner-card__header.is-purple h4::before{background-image:url(\"data:image/svg+xml,%3Csvg width='21' height='23' viewBox='0 0 21 23' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M20.0375 12.8374C20.1644 12.439 20.2172 12.0289 20.2077 11.6237C20.193 11.3305 20.1548 11.0373 20.0712 10.7441C19.8196 9.83306 19.223 9.01989 18.3294 8.50724L5.61817 1.2017C3.82388 .173815 1.53618 .784335 .506483 2.56804C-.533615 4.34915 .0797871 6.62351 1.87408 7.65398L8.97715 11.7427L1.87408 15.8201C.0797871 16.8527 -.531016 19.1271 .506483 20.9156C1.53618 22.6941 3.82388 23.302 5.61817 22.2746L18.3294 14.9643C19.1871 14.4728 19.7693 13.7027 20.0375 12.8374Z' fill='white'/%3E%3C/svg%3E%0A\")}.sf-blue-mountains{background-size:90% auto;background-repeat:no-repeat;background-position:center bottom;background-image:url(\"data:image/svg+xml,%3Csvg width='1361' height='410' viewBox='0 0 1361 410' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M1360.25 410L1065.53 114.309L976.256 203.875L773.049 0L364.393 410H1360.25Z' fill='%233AA8DF'/%3E%3Cpath d='M274.778 410L137.467 272.238L.15625 410H274.778Z' fill='%233AA8DF'/%3E%3C/svg%3E%0A\")}.bwalignr,.main-pr-body .bwalignr{text-align:right}.bwblockalignl{margin-left:0;margin-right:auto}.bwcellpmargin{margin-top:0;margin-bottom:0}.bwlistdisc{list-style-type:disc}.bwpadb3{padding-bottom:4px}.bwpadb4{padding-bottom:5px}.bwpadl0{padding-left:0}.bwpadl3{padding-left:15px}.bwpadl6{padding-left:30px}.bwpadl9{padding-left:45px}.bwpadl12{padding-left:60px}.bwpadr0{padding-right:0}.bwtablemarginb{margin-bottom:10px}.bwvertalignb{vertical-align:bottom}.bwvertalignt{vertical-align:top}.bwsinglebottom{border-bottom:1pt solid #000}.bwdoublebottom{border-bottom:2.25pt double #000}.bwwidth1{width:1%}.bwwidth2{width:2%}.bwwidth6{width:6%}.bwwidth7{width:7%}.bwwidth8{width:8%}.bwwidth10{width:10%}.bwwidth12{width:12%}.bwwidth32{width:32%}.bwwidth44{width:44%}.bwwidth72{width:72%}.bwwidth97{width:97%}.main-pr-body{font-size:18px;line-height:26px}.main-pr-body img{display:block;width:100%;height:auto!important;border-radius:var(--small-border-radius)}.main-pr-body table{width:100%;display:block}.main-pr-body tbody{background-color:#f7f7f7}.main-pr-body .bwsinglebottom{border-bottom:1pt solid #000!important}.main-pr-body td.bwwidth44{padding-right:40px}.main-pr-body .bw-release-story{font-family:Lato,sans-serif}.main-pr-body .bw-release-story sup,.snowflake-mega-nav-dropdown-header-content-right a{white-space:nowrap}.main-pr-body .bw-release-story\u003E*,.main-pr-body\u003Espan\u003E*{margin-bottom:2rem!important}.snowflake-text.main-pr-body tbody,.snowflake-text.main-pr-body tbody p{font-size:14px!important;line-height:20px!important;width:100%;display:block}.press-body .snowflake-flexible-column-container-items{gap:var(--spacing-08)}.about-snowflake{border:1px solid #ccc;background-color:var(--ui-background-05);padding:24px;border-radius:8px;margin-top:0}.about-snowflake__logo{max-width:140px;margin-top:16px}.hero--press .snowflake-hero-system-inner{max-width:1408px;margin:0 auto!important}#arcticNavItem{flex-direction:column}#arcticNavItem::before{content:\"Featured Open Source Technologies\";display:block;margin-top:48px;margin-bottom:24px;font-size:16px!important;line-height:16px!important;font-weight:800!important;text-transform:uppercase}@media screen and (min-width:768px){.sc-hero__inner\u003E.snowflake-flexible-column-container-items\u003Ediv:last-child{position:relative;height:100%;top:auto;left:auto;width:auto}.sc-hero__inner\u003E.snowflake-flexible-column-container-items\u003Ediv:last-child::before{background:linear-gradient(180deg,#202c35 -7.5%,#fff0 51.25%,#202c35 107.69%)}.sc-hero__byline\u003Espan{display:flex;flex-wrap:wrap}.sc-hero__byline p:not(:last-child)::after{content:\"|\";margin:0 12px;opacity:.5}.sc-hero__button-container .snowflake-flexible-column-container-items{position:absolute;bottom:0;padding:0;margin:0 24px 0 0}.sc-hero__button-container .hero-watch-the-demo{padding:12px 16px!important;float:right;margin-bottom:48px;background-color:rgb(35 45 54 / .8)}.summit-overview-stat{padding:0 40px}.summit-timeline{border-bottom:3px solid var(--ui-01);margin-bottom:64px}.summit-add-on-block__content,.summit-pricing-block__content{padding:0 40px 40px}#arcticNavItem::before{font-size:12px!important;margin-bottom:8px;margin-top:16px}.snowflake-mega-nav-nav-item-title-wrapper\u003E.snowflake-mega-nav-nav-item-title{line-height:20px!important}.snowflake-card .heading-2.snowflake-title-line{font-size:24px!important;line-height:28px!important}}@media screen and (min-width:992px){.hp-hero__eyebrow a{gap:12px;margin-left:0;margin-right:0}.hp-hero__eyebrow a::after{content:\"\";background-image:url(\"data:image/svg+xml,%3Csvg width='6' height='11' viewBox='0 0 6 11' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M5.49134 5.79438C5.53447 5.75922 5.56923 5.71489 5.5931 5.66463C5.61697 5.61436 5.62935 5.55941 5.62935 5.50376C5.62935 5.44811 5.61697 5.39316 5.5931 5.34289C5.56923 5.29263 5.53447 5.2483 5.49134 5.21314L.736339 .413136C.522589 .203135 .331339 .203135 .151339 .413136C-.0286612 .623135 -.0586612 .818135 .151339 .994386L4.48634 5.50188L.155089 9.97938C.107068 10.0142 .0679743 10.0598 .0410153 10.1126C.0140562 10.1654 0 10.2238 0 10.2831C0 10.3424 .0140562 10.4009 .0410153 10.4537C.0679743 10.5065 .107068 10.5521 .155089 10.5869C.335089 10.7969 .530089 10.7969 .740089 10.5869L5.49134 5.79438Z' fill='black'/%3E%3C/svg%3E%0A\");display:inline-block;width:12px;height:12px;background-repeat:no-repeat;background-size:auto 100%;background-position:left center}.promo-banner--homepage{padding-top:32px}.homepage-banner-offset-container::after{height:50%}#storyHighlights{padding:2rem}.body-display-v2.snowflake-quote-item-quote-text{line-height:28px!important}.snowflake-hero-system-headline .heading-1-v2{line-height:48px;font-size:54px!important}.sc-overview__webinar-promo-banner .snowflake-content-chip-content{flex-direction:row;justify-content:space-between;align-items:center;width:100%}.sc-overview__webinar-promo-banner .snowflake-content-chip-content .heading-5-v2{flex-direction:row}.sc-overview__webinar-promo-banner .snowflake-content-chip-content .snowflake-title-v2-line:not(:first-child)::before{content:\"|\";margin:0 6px}.sc-cert-banner{padding:40px}.sc-cert-banner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{margin:0!important;width:50%}.sc-cert-banner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{flex-grow:1;padding-right:24px}.sc-cert-banner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:last-child{max-width:240px}.summit-pricing-block__content\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:last-child{width:70%;padding-left:40px}.summit-pricing-block__content\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{width:30%}.summit-add-on-block__content\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(33.3333% - 24px);margin:0!important;display:flex}.summit-pricing-block__tile .snowflake-content-chip-content{display:flex;flex-direction:row;align-items:center;width:calc(100% - 200px)}.summit-pricing-block__tile .heading-5-v2 span.snowflake-title-v2-line:last-child{position:absolute;top:50%;transform:translate(0,-50%);right:40px}.press-body\u003E.snowflake-flexible-column-container-items\u003Ediv:last-child{position:sticky;top:120px}.snowflake-mega-nav-navigation-title:hover{color:var(--ui-01)}}@media screen and (min-width:1024px){.about-snowflake{padding:28px}.about-snowflake__logo{max-width:none;padding:0 0 0 48px;margin-bottom:0}.hero--press .snowflake-hero-system-layout-70-30 .snowflake-hero-system-content-container{width:85%}.snowflake-hero-system{padding-bottom:var(--spacing-04);padding-top:var(--spacing-07)}.hero--press .display-2-v2{font-size:64px;line-height:56px}.about-snowflake\u003E.container\u003E.cmp-container\u003E.aem-container{flex-direction:row;flex-wrap:nowrap;align-items:center}.about-snowflake\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:last-child{max-width:280px}.about-snowflake\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{flex-grow:1;margin-bottom:0!important}#polarisNavItem{margin-top:40px}.snowflake-mega-nav-nav-item-description{line-height:18px!important}.snowflake-mega-nav-column-items{gap:var(--spacing-01);grid-gap:var(--spacing-01)}.snowflake-mega-nav-navigation-title{text-transform:none}}div[id*=blueIcon] .snowflake-mega-nav-nav-item-icon__inner{background:var(--ui-01);padding:8px}div[id*=blueIcon]:hover .snowflake-mega-nav-nav-item-icon__inner{background:var(--ui-01)!important}.snowflake-mega-nav-nav-item-icon__inner{border-radius:4px;background:var(--ui-background-05);padding:6px}.snowflake-mega-nav-nav-item:hover .snowflake-mega-nav-nav-item-icon__inner{background:#fff!important}.snowflake-mega-nav-nav-item-icon.snowflake-image-container{height:40px;width:40px}.snowflake-mega-nav-dropdown-footer-links\u003E.snowflake-button-link\u003E.snowflake-button-container{font-size:16px!important;font-family:Texta!important;font-weight:800!important}.snowflake-mega-nav-dropdown-footer-icon.snowflake-image-container{margin-right:8px;width:40px!important;height:40px!important}#viewAllCapabilities a:hover{background:0 0!important}#platformFooter .snowflake-title-v2 .snowflake-title-v2-line:last-child{font-family:Lato;font-size:14px;font-weight:500}#platformFooter .snowflake-mega-nav-dropdown-footer-links{flex-grow:1;justify-content:flex-end;align-items:center}#platformFooter .snowflake-mega-nav-dropdown-footer-content{flex-direction:row}#offset,#open-source{flex-direction:column;border-top:1px solid #ccc}#offset::before,#open-source::before{content:\" \";display:block;width:100%;font-weight:800!important;font-size:12px!important;line-height:14px;text-transform:uppercase;white-space:nowrap;margin-top:16px;margin-bottom:8px}#open-source::before{content:\"Open Source Technologies\"}.snowflake-mega-nav-dropdown-menu-close-button{margin:var(--spacing-04) 0 var(--spacing-03)}.snowflake-mega-nav-column{gap:var(--spacing-02)!important}.snowflake-mega-nav-nav-item\u003Ea{width:100%;margin-left:-8px;padding:8px;border-radius:4px}.snowflake-mega-nav-nav-item\u003Ea:hover{background-color:var(--ui-background-05)}.snowflake-mega-nav-nav-item-description{margin-top:2px;display:block}#promobanner_overflowBottomDarkBlue::before{content:'';display:block;position:absolute;bottom:0;left:0;width:100%;height:50%;background:#212d35}#promobanner_overflowTopDarkBlue::before{content:'';display:block;position:absolute;top:0;left:0;width:100%;height:50%;background:#212d35}.overview-card\u003Ediv{box-shadow:0 0 14px 0 rgba(0,0,0,.10);background-color:#fff;border-radius:16px;overflow:hidden}.overview-card-text{padding:40px}.overview-card-image img{border-radius:0 !important}.overview-card-text h3,.overview-card-text .heading-3-v2{font-size:18px;line-height:1.1;margin-top:0}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"},"mega_header":{"additionalClasses":"heap-nav-header","layout":"SIMPLE","id":"container-27ca8c2578",":items":{"nav_mega":{"activeItem":"item_1719963657751_c_663444255","id":"tabs-501fd3922b",":type":"snowflake-site/components/nav/nav-mega",":items":{"item_1719963657751_c_663444255":{"id":"nav-dropdown-menu-f3056aa369","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-38bebf9720",":items":{"nav_column":{"additionalClasses":"nav-platform-sidebar","numberOfSubColumns":"one-column","minWidth":"230","maxWidth":"350","layout":"SIMPLE","id":"container-2b34ddfdea",":items":{"nav_item_copy_copy_2_793631646":{"id":"nav-item-60948c0e74","additionalClasses":"nav-item__platform-parent is-platform","linkDescription":"Develop AI products, apps and more on a fully managed platform that securely connects businesses globally — across any type or scale of data.","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/platform/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"The Snowflake Platform"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-b1fc67d363","additionalClasses":"nav-item nav-item--si is-si","linkDescription":"All your knowledge. One trusted enterprise agent.","flag":"NOW GA","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/snowflake-cowork/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake CoWork"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2_836345186":{"id":"nav-item-1a177b259f","additionalClasses":"blue-icon is-analytics","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/analytics/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Analytics"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2":{"id":"nav-item-c3da78211b","additionalClasses":"blue-icon is-ai","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/ai/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"AI"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2_1314771042":{"id":"nav-item-e099bfdc27","additionalClasses":"blue-icon is-data-eng","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/data-engineering/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Data Engineering"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634":{"id":"nav-item-0a2e3d3d58","additionalClasses":"blue-icon is-apps-collab","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/applications-and-collaboration/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Applications & Collaboration"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634_2013333117":{"id":"nav-item-a30fe7578b","additionalClasses":"blue-icon is-transactions","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/transactions/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Transactions"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_copy_2_793631646","nav_item","nav_item_copy_copy_2_836345186","nav_item_copy_copy_2","nav_item_copy_copy_2_1314771042","nav_item_copy_144634","nav_item_copy_144634_2013333117"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy":{"additionalClasses":"meganav-platform-features","navColumnTitle":"Featured Capabilities","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-afd8f61efc",":items":{"nav_item_copy_212715":{"id":"nav-item-b6f3ff5ab4","additionalClasses":"is-cortex-code","linkDescription":"Snowflake-native AI coding agent ","flag":"New","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/snowflake-coco/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake CoCo"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-e8287e7f2c","additionalClasses":"is-cortex-ai","linkDescription":"Instant access to industry-leading LLMs","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/cortex/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Cortex AI"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590635":{"id":"nav-item-ce42f1d40d","additionalClasses":"is-marketplace","linkDescription":"Third-party data sources connected within minutes","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/marketplace/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Marketplace"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590":{"id":"nav-item-5d13b6ecda","additionalClasses":"is-snowpark","linkDescription":"Libraries and code execution environments that run Python and more","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/snowpark/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Snowpark"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590_983061516":{"id":"nav-item-59c7f5bef3","additionalClasses":"is-streamlit","linkDescription":"Framework for transforming Python scripts into web apps","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/streamlit-in-snowflake/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Streamlit"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_212715","nav_item","nav_item_copy_660590635","nav_item_copy_660590","nav_item_copy_660590_983061516"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_692142673":{"navColumnTitle":" ","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-ba8d19720e",":items":{"nav_item_copy_660590_1739526127":{"id":"nav-item-cc110c7a44","additionalClasses":"is-postgres","linkDescription":"Fully compatible open source Postgres running on Snowflake","flag":"Now GA","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/postgres/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Postgres"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_185565":{"id":"nav-item-31a9ec8397","additionalClasses":"is-dcr","linkDescription":"Streamlined model development and MLOps from a centralized UI","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/end-to-end-ml-workflows/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake ML"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_212715":{"id":"nav-item-c8fc9271ab","additionalClasses":"is-openflow","linkDescription":"Effortless data movement for integrations","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/openflow/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Openflow"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590":{"id":"nav-item-6d2e295a6d","additionalClasses":"is-notebooks","linkDescription":"Interactive dev environment for data and AI teams","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/notebooks/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Notebooks"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_258535199":{"id":"nav-item-f8a098a546","propertiesId":"workload-nav-1","additionalClasses":"is-native-apps","linkDescription":"End-to-end, Snowflake-native app creation and distribution","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/product/features/native-apps/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Native Apps"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_660590_1739526127","nav_item_copy_185565","nav_item_copy_212715","nav_item_copy_660590","nav_item_258535199"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_782221091":{"navColumnTitle":" ","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-f980d43813",":items":{"nav_item_copy":{"id":"nav-item-6ed42c1f4b","additionalClasses":"is-light-gray-icon is-horizon-catalog","linkDescription":"Universal AI catalog","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/horizon/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Horizon Catalog"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590_1293798742":{"id":"nav-item-097296659d","additionalClasses":"is-snowflake-ml","linkDescription":"Governed context layer that keeps AI, BI and data apps working from one truth","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/horizon-context/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Horizon Context"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_511717659_c":{"id":"nav-item-44c204e592","additionalClasses":"is-unistore","linkDescription":"Unify transactional and analytical workloads in Snowflake for enhanced simplicity","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/unistore/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Unistore"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_511717659_c_1443811525":{"id":"nav-item-0cbf711503","additionalClasses":"is-observe","linkDescription":"AI-powered observability for faster production troubleshooting","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/observe/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Observe"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_511717659_c_1006104884":{"id":"nav-item-f906e144d9","additionalClasses":"is-observe","linkDescription":"Use any engine on a single governed data copy","flag":"Now GA","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/use-cases/interoperable-lakehouse/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Interoperable Lakehouse"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy","nav_item_copy_660590_1293798742","nav_item_511717659_c","nav_item_511717659_c_1443811525","nav_item_511717659_c_1006104884"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column","nav_column_copy_copy","nav_column_692142673","nav_column_782221091"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Product"},"nav_dropdown_menu_2":{"id":"nav-dropdown-menu-4721d02c59","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-26f7381303",":items":{"nav_column":{"navColumnTitle":"INDUSTRIES","numberOfSubColumns":"one-column","minWidth":"280","layout":"SIMPLE","id":"container-ef80a5b3fb",":items":{"nav_item_copy_361384_2056203141":{"id":"nav-item-6c23b52785","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"All Industries"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-973d113ca9","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/advertising-media-entertainment/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Advertising, Media & Entertainment"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-d932ada554","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/financial-services/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Financial Services"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-7f1ffdb165","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/healthcare-and-life-sciences/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Healthcare & Life Sciences"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1533429516":{"id":"nav-item-9c7099214f","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/manufacturing/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Manufacturing"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1444458226":{"id":"nav-item-0668ee1b17","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/public-sector/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Public Sector"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1149488919":{"id":"nav-item-1ddbc0946d","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/retail-consumer-goods/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Retail & Consumer Goods"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_57417040":{"id":"nav-item-611ea535ba","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/technology/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Technology"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_361384674":{"id":"nav-item-6fa461ab9e","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/telecom/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Telecom"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_361384":{"id":"nav-item-0dcb437c3b","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/industries/travel-hospitality/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Travel & Hospitality"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_361384_2056203141","nav_item","nav_item_copy","nav_item_copy_1970515619","nav_item_copy_1533429516","nav_item_copy_1444458226","nav_item_copy_1149488919","nav_item_copy_57417040","nav_item_copy_361384674","nav_item_copy_361384"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy":{"navColumnTitle":"DEPARTMENTS","numberOfSubColumns":"one-column","minWidth":"160","layout":"SIMPLE","id":"container-085e191e86",":items":{"nav_item":{"id":"nav-item-a20632d42d","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/solutions/departments/finance/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Finance"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-dfd412f002","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/solutions/departments/information-technology/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"IT"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-964f898fb9","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/solutions/departments/marketing/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Marketing"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy","nav_item_copy_1970515619"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_833417450":{"navColumnTitle":"Enablement Solutions","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-641010f2ae",":items":{"nav_item_copy_107772":{"id":"nav-item-39a17ea013","linkDescription":"Confident migration to a unified platform","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/migrate-to-the-cloud/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Migrate to the AI Data Cloud"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Cloud icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/nav_dropdown_menu_2/nav_column_container/nav_column_833417450/nav_item_copy_107772/icon.coreimg.svg/1723828484100/nav-icon-cloud.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy":{"id":"nav-item-8d4c029066","linkDescription":"Snowflake experts to help you accelerate and achieve business goals","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/services-delivery/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Services Delivery"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Migrate icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/nav_dropdown_menu_2/nav_column_container/nav_column_833417450/nav_item_copy_copy/icon.coreimg.svg/1768354429188/nav-icon--migrate.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_107772","nav_item_copy_copy"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy":{"navColumnTitle":"PARTNER SOLUTIONS","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-234e4708ac",":items":{"nav_item":{"id":"nav-item-6219a56f36","linkDescription":"Programs with product, solutions and cloud partners","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/partners/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake Partner Network"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Partner Network icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/nav_dropdown_menu_2/nav_column_container/nav_column_copy_copy/nav_item/icon.coreimg.svg/1723828498700/nav-icon--partner-network.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-22aa92be1c","linkDescription":"Partners, apps and solutions for enhanced deployment","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/partners/all-partners/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Partner Finder"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Partner Finder icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/nav_dropdown_menu_2/nav_column_container/nav_column_copy_copy/nav_item_copy/icon.coreimg.svg/1726173927645/nav-icon--partner-finder.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-cecd2bdf03","linkDescription":"Live and virtual events","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/partners/event-partnership-opportunities/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Event Partnership Opportunities"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Calendar icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/nav_dropdown_menu_2/nav_column_container/nav_column_copy_copy/nav_item_copy_1970515619/icon.coreimg.svg/1726173935655/nav-icon--events.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy","nav_item_copy_1970515619"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column","nav_column_copy","nav_column_833417450","nav_column_copy_copy"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Solutions"},"item_1719963657751_c":{"id":"nav-dropdown-menu-3cafd164fb","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-00433fc4d2",":items":{"nav_column":{"numberOfSubColumns":"one-column","minWidth":"230","maxWidth":"350","layout":"SIMPLE","id":"container-d9439936ab",":items":{"nav_item_copy_copy_2_793631646":{"id":"nav-item-a3177bc09f","additionalClasses":"nav-item__platform-parent-why-sf","linkDescription":"Collaborate locally and globally to reveal new insights, create previously unforeseen business opportunities, and identify your customers with seamless experiences.","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Why Snowflake"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_copy_2_793631646"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy":{"additionalClasses":"meganav-platform-features","numberOfSubColumns":"two-columns","maxWidth":"1200","layout":"SIMPLE","id":"container-aa4611c3c3",":items":{"nav_item":{"id":"nav-item-1285fa1ea4","propertiesId":"testID","linkDescription":"Case studies and videos showcasing how global organizations use Snowflake","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/customers/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Customers"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Customer icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item/icon.coreimg.svg/1739839279367/nav-icon--partner-network.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_258535199":{"id":"nav-item-8328ce6bc5","propertiesId":"workload-nav-1","linkDescription":"Learn how to connect, share and integrate the data and apps on the AI Data Cloud","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/what-is-data-cloud/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"The AI Data Cloud Explained"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Cloud icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item_258535199/icon.coreimg.svg/1739840490955/nav-icon-cloud.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_185565":{"id":"nav-item-5d217e18fe","linkDescription":"Comprehensive security through built-in features, robust cloud infrastructure protection, and more","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/snowflake-security-hub/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Security Hub"},"icon":{"id":"icon","lazyEnabled":true,"alt":"User with security lock icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item_copy_185565/icon.coreimg.svg/1758909528089/user-security-admins-ciso-icon.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-f5f827a21f","additionalClasses":"is-light-gray-icon","linkDescription":"Maximize economic value through minimizing TCO and continuously optimizing price for performance","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/pricing-options/cost-and-performance-optimization/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Cost and Performance Optimization"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Cost Optimization icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item_copy/icon.coreimg.svg/1758909542267/nav-icon-cost-optimization-performance.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_185565_903555964":{"id":"nav-item-daca004db9","linkDescription":"Startups building applications in the AI Data Cloud","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/startup-program/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake for Startups"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Launch","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item_copy_185565_903555964/icon.coreimg.svg/1758732224323/launch.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_258535199","nav_item_copy_185565","nav_item_copy","nav_item_copy_185565_903555964"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column","nav_column_copy_copy"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Why Snowflake"},"item_1719961362824":{"id":"nav-dropdown-menu-caa6187663","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-6ced7341a7",":items":{"nav_column_copy":{"navColumnTitle":"Connect","numberOfSubColumns":"one-column","minWidth":"124","layout":"SIMPLE","id":"container-61006c2e4b",":items":{"nav_item":{"id":"nav-item-e93a0bc833","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Blog"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_180298689":{"id":"nav-item-81ac8f0ff6","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/events/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Events"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_1639361946":{"id":"nav-item-c73cd1caa8","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/support/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Support"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_680912746":{"id":"nav-item-3684fd2b69","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/contact/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Contact us"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_180298689","nav_item_1639361946","nav_item_680912746"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_44600420__826130542":{"navColumnTitle":"Learn","numberOfSubColumns":"two-columns","layout":"SIMPLE","id":"container-f305db357d",":items":{"nav_item_copy":{"id":"nav-item-81d1d97b87","linkDescription":"Ebooks, videos, white papers and more","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/resources/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Resource Library"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Notebooks icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy/icon.coreimg.svg/1736877128196/nav-icon--notebooks.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-3eb4b2a097","linkDescription":"Overview of Snowflake's educational offerings","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/resources/learn/training/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Training"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Training icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item/icon.coreimg.svg/1722385094416/nav-icon--training.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634_1984107859":{"id":"nav-item-9a156e9ddd","linkDescription":"Expert-led discussions and demos across industries and use cases","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/webinars/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Webinars"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Webinars icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_144634_1984107859/icon.coreimg.svg/1759424691990/nav-icon--webinars.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1438098918":{"id":"nav-item-b5eb770164","linkDescription":"Snowflake's technical industry professional certifications","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/resources/learn/certifications/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Certifications"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Certification icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_1438098918/icon.coreimg.svg/1722382780833/nav-icon--cert.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_143809":{"id":"nav-item-bb45ef2ab4","linkDescription":"Weekly product demos showcasing key features and live Q&A ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/webinars/demo/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Live Demos"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Live Demo icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_143809/icon.coreimg.svg/1759424359543/nav-icon--live-demo.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_333890638":{"id":"nav-item-54f8a62b75","linkDescription":"Training courses for all levels, on-demand or instructor-led","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://learn.snowflake.com/en/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Snowflake University"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Education icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_333890638/icon.coreimg.svg/1722382769808/nav-icon--education.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_189945":{"id":"nav-item-447244a2fc","linkDescription":"Instructor-led virtual workshops for exploring key Snowflake features","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/webinars/virtual-hands-on-lab/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Hands-On Labs"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Hands-on Labs icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_189945/icon.coreimg.svg/1759388182903/nav-icon--labs.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_333890":{"id":"nav-item-566f246fd7","linkDescription":"Academic papers written by Snowflake researchers","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/resources/publications/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake Research Publications"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Copy","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_333890/icon.coreimg.svg/1756326371387/copy.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_333890_930852828":{"id":"nav-item-4ceeed3dfb","linkDescription":"Informative articles about AI and data topics","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/fundamentals/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Fundamentals"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Document with list","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_copy_333890_930852828/icon.coreimg.svg/1756853637155/data-sheet.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy","nav_item","nav_item_copy_144634_1984107859","nav_item_copy_1438098918","nav_item_copy_143809","nav_item_copy_333890638","nav_item_copy_189945","nav_item_copy_333890","nav_item_copy_333890_930852828"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column_copy","nav_column_44600420__826130542"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},"nav_promo_section":{"id":"nav-promo-section-8fe1ca50ae","experience_fragment_1":{"id":"experiencefragment-8fb90319b6","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/master1/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"nav_promo_card":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-30a12cb2c6",":items":{"nav_promo_card":{"id":"nav-promo-card-95cf4b83a9","openInNewWindow":true,"layout":"horizontal","headline":"Dev Day Virtual - June 25","description":"Don’t just hear about AI — build it. Luminary talks and hands-on labs","linkTitle":"Learn more","linkUrl":"/en/dev-day/americas-virtual/","image":{"id":"image","lazyEnabled":true,"alt":"dev day","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--de231e36-6645-4550-abd9-0f8de758ac66/web-dev-day-26-960x540-1x.png?quality=85&preferwebp=true","width":"960","height":"540",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-promo-card"}},":itemsOrder":["nav_promo_card"],":type":"snowflake-site/components/container"},"cq:metadata":{":type":"nt:unstructured"}},":itemsOrder":["root","cq:metadata"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"experience_fragment_2":{"id":"experiencefragment-79984eb935","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/navigation-promo-card-2/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"nav_promo_card":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-87ded7ec82",":items":{"nav_promo_card":{"id":"nav-promo-card-bfc0719a7a","openInNewWindow":true,"layout":"horizontal","headline":"The ROI of Gen AI and Agents 2026","description":"Discover how 92% of early adopters are achieving positive ROI with gen AI.","linkTitle":"Learn More","linkUrl":"/en/lp/radical-roi-generative-ai/","image":{"id":"image","lazyEnabled":true,"alt":"roi of gen ai and agents","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--0c15edae-1a97-4739-8b16-c7f3941a6d9e/web-roi-of-gen-ai-and-agents-2026-r02-960x540.png?quality=85&preferwebp=true","width":"960","height":"540",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-promo-card"}},":itemsOrder":["nav_promo_card"],":type":"snowflake-site/components/container"},"cq:metadata":{":type":"nt:unstructured"}},":itemsOrder":["root","cq:metadata"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"experience_fragment_3":{"id":"experiencefragment-ee5c17d387","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/navigation-promo-card-3/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"nav_promo_card":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-37b187fd67",":items":{"nav_promo_card":{"id":"nav-promo-card-f8a6a5dbd2","openInNewWindow":true,"layout":"horizontal","headline":"Startup 2026: AI Agents Mean Business","description":"Venture leaders weigh in on agentic AI. ","linkTitle":"Learn more","linkUrl":"/en/lp/building-startup-ai-age/","image":{"id":"image","lazyEnabled":true,"alt":"alt","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--a320b404-dca1-4477-b033-c79708538657/web-startup-2026-960x540.png?quality=85&preferwebp=true","width":"960","height":"540",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-promo-card"}},":itemsOrder":["nav_promo_card"],":type":"snowflake-site/components/container"},"cq:metadata":{":type":"nt:unstructured"}},":itemsOrder":["root","cq:metadata"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},":type":"snowflake-site/components/nav/nav-promo-section"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Resources"},"item_1719963657751":{"id":"nav-dropdown-menu-ad4a8df75a","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-5b7c20b9cb",":items":{"nav_column_copy_copy":{"navColumnTitle":"Build","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-2c4bdc991f",":items":{"nav_item":{"id":"nav-item-c93cc200f2","propertiesId":"testID","linkDescription":"Overview of the dev resources you need to build and scale","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Snowflake for Developers"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Developers icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy/nav_item/icon.coreimg.svg/1731362494574/nav-icon--devs.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1855651246":{"id":"nav-item-733679a4cc","linkDescription":"Reference architectures, use cases and best practices","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/guides/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Developer Guides"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Solution Center icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy/nav_item_copy_1855651246/icon.coreimg.svg/1761677891705/nav-icon--solution-center.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-89c62d32e2","additionalClasses":"is-light-gray-icon","linkDescription":"The latest software versions, drivers, libraries and relevant docs","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/downloads/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Downloads"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Download icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy/nav_item_copy/icon.coreimg.svg/1731362660050/nav-icon-download.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy_1855651246","nav_item_copy"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy_1367930678":{"navColumnTitle":"Learn","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-313cd9e1a3",":items":{"nav_item":{"id":"nav-item-5c9ef8ad2b","propertiesId":"testID","linkDescription":"Reference docs, guides, tutorials and announcements","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://docs.snowflake.com/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Documentation"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Docs icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy_1367930678/nav_item/icon.coreimg.svg/1731361950527/nav-icon--docs.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-f13e3d90d3","additionalClasses":"is-light-gray-icon","linkDescription":"Key projects Snowflake engineers maintain and support","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/open-source/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Open Source"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Open Source icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy_1367930678/nav_item_copy/icon.coreimg.svg/1731365437016/nav-icon-open-source.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy":{"id":"nav-item-0606fcac50","additionalClasses":"is-light-gray-icon","linkDescription":"Online and in-person classes and workshops to upskill on Snowflake","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/northstar/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Builder Education"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Northstar logo","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy_1367930678/nav_item_copy_copy/icon.coreimg.svg/1731362475640/nav-icon--northstar.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy","nav_item_copy_copy"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy_1101894776":{"navColumnTitle":"Connect","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-896bf20c82",":items":{"nav_item":{"id":"nav-item-04438cb68c","propertiesId":"testID","linkDescription":"Snowflake’s technical leaders on what, why and how they build features","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/engineering-blog/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Engineering Blog"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Developers icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy_1101894776/nav_item/icon.coreimg.svg/1757101368571/nav-icon--developer-center.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1855651246":{"id":"nav-item-fb585721d2","linkDescription":"Tips, tricks and discussion with fellow Snowflake developers","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://community.snowflake.com/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Community"},"icon":{"id":"icon","lazyEnabled":true,"alt":"Partner Network icon","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751/nav_column_container/nav_column_copy_copy_1101894776/nav_item_copy_1855651246/icon.coreimg.svg/1731362644348/nav-icon--partner-network.svg",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy_1855651246"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column_copy_copy","nav_column_copy_copy_1367930678","nav_column_copy_copy_1101894776"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},"nav_promo_section":{"id":"nav-promo-section-fddcf8767b","experience_fragment_1":{"id":"experiencefragment-4719694d23","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/nav-promo-5/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"nav_promo_card":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-38aac87333",":items":{"nav_promo_card":{"id":"nav-promo-card-0678d461dd","openInNewWindow":false,"layout":"horizontal","headline":"Get started with your first Snowflake Notebook","description":"Write and execute code, visualize results, and tell the story of your analysis all in one place.","linkTitle":"Learn More","linkUrl":"/en/developers/solutions-center/getting-started-with-your-first-snowflake-notebook-project/","image":{"id":"image","lazyEnabled":true,"alt":"alt","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--dc7e334a-c38b-4283-b1de-fcf829952eef/nav-promo-first-notebook.jpg?quality=85&preferwebp=true","width":"415","height":"210",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-promo-card"}},":itemsOrder":["nav_promo_card"],":type":"snowflake-site/components/container"},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/nav-promo-card-4",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"experience_fragment_2":{"id":"experiencefragment-99b38be6f3","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/nav-promo-card-4/jcr:content","configured":true,":items":{"root":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"nav_promo_card":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-fc6388077f",":items":{"nav_promo_card":{"id":"nav-promo-card-8441824674","openInNewWindow":true,"layout":"horizontal","headline":"Northstar Builder Workshops","description":"Join other developers as you roll up your sleeves and explore the possibilities of Snowflake.","linkTitle":"Learn More","linkUrl":"/en/nav-promos/northstar-builders-workshop/","image":{"id":"image","lazyEnabled":true,"alt":"Snowflake Northstar logo","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--14341ced-bc5e-4a29-9762-b7857f6cadfc/nav-promo-northstar.jpg?quality=85&preferwebp=true","width":"1440","height":"700",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-promo-card"}},":itemsOrder":["nav_promo_card"],":type":"snowflake-site/components/container"},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/en/site/nav-promo-card/master",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},":type":"snowflake-site/components/nav/nav-promo-section"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Developers"},"item_1718247180324":{"id":"nav-dropdown-menu-67cb42685b","enableDropdown":false,"link_url":"/en/pricing-options/",":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"Pricing"}},":itemsOrder":["item_1719963657751_c_663444255","nav_dropdown_menu_2","item_1719963657751_c","item_1719961362824","item_1719963657751","item_1718247180324"]},"languagenavigation":{"id":"language-navigation-ba293225da","languageNavItems":[{"title":"English","path":"/en/developers/guides/data-engineering-with-notebooks/","locale":"en","active":true},{"title":"日本語","path":"/ja/","locale":"ja","active":false},{"title":"한국어","path":"/ko/","locale":"ko","active":false},{"title":"中文（简体）","path":"/zh_cn/","locale":"zh-cn","active":false},{"title":"Português","path":"/pt_br/","locale":"pt-br","active":false},{"title":"Deutsch","path":"/de/","locale":"de","active":false},{"title":"Français","path":"/fr/","locale":"fr","active":false},{"title":"Español","path":"/es/","locale":"es","active":false},{"title":"Italiano","path":"/it/","locale":"it","active":false}],":type":"snowflake-site/components/nav/language-navigation"},"button_1177328691":{"id":"button-bbd0d1b73d","heapButtonClasses":["mega-nav__sign-in"],"showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://app.snowflake.com/"},"linkTargetContentType":"GENERIC","appliedCssClassNames":"snowflake-button-link snowflake-button-black snowflake-button-compact","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Sign in"},"button":{"id":"button-60190fab87","heapButtonClasses":["contact_nav","heap-nav-contact"],"showOutboundIcon":true,"buttonLink":{"valid":true,"url":"/en/contact-sales/"},"linkTargetContentType":"GENERIC","appliedCssClassNames":"snowflake-button-secondary snowflake-button-blue snowflake-button-compact","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"CONTACT SALES"},"button_288358396":{"id":"button-8d926025d5","heapButtonClasses":["start_for_free_nav","heap-nav-start-for-free"],"showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://signup.snowflake.com/"},"linkTargetContentType":"GENERIC","appliedCssClassNames":"snowflake-button-primary snowflake-button-blue snowflake-button-compact","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"start for free"}},":itemsOrder":["nav_mega","languagenavigation","button_1177328691","button","button_288358396"],"appliedCssClassNames":"snowflake-header-container white",":type":"snowflake-site/components/mega-header"}},":itemsOrder":["markup_editor","mega_header"],":type":"snowflake-site/components/container"},"image":{":type":"nt:unstructured"},"cq:targetMetadata":{"cq:targetStatus":"OUT_OF_SYNC","cq:exportTime":1781280015540,"cq:targetOfferId":860250,":type":"nt:unstructured"}},":itemsOrder":["root","image","cq:targetMetadata"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"markup_editor_1950346551":{"id":"markup-editor-95ec166912","title":" ","cssContent":".snowflake-markdown-table code[class*=language-],.snowflake-markdown-table code[class*=language-],.snowflake-markdown .snowflake-text code[class*=language-],.snowflake-markdown .snowflake-text pre[class*=language-]{background-color:rgba(var(--ui-12-rgb),.5);color:var(--text-01);text-shadow:none;padding:var(--spacing-00);border-radius:var(--spacing-00);font-size:smaller}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"},"responsivegrid":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"quickstart_hero":"aem-GridColumn aem-GridColumn--default--12","flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"columnCount":12,":items":{"quickstart_hero":{"id":"quickstart-hero-67b7ba8180","quickstartHeroTitle":{"lines":["Getting Started with Data Engineering using Snowflake Notebooks"],"type":"heading2",":type":"snowflake-site/components/title-v2"},"quickstartHeroAuthor":"Jeremiah Hansen","quickstartHeroForkRepoLink":{"id":"button-685cf5f4f7","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://github.com/Snowflake-Labs/sfquickstarts/tree/master/site/sfguides/src/data-engineering-with-notebooks"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"Fork Repo"},"quickstartHeroBreadcrumbs":[{"title":"Getting Started with Data Engineering using Snowflake Notebooks","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides/data-engineering-with-notebooks","currentPage":true},{"title":"Guides","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers/guides","currentPage":false},{"title":"Snowflake for Developers","url":"https://www.snowflake.com/content/snowflake-site/global/en/developers","currentPage":false}],"quickstartHeroFirstCertifiedTag":{"tagText":"Community Solution","tagColor":"#29B5E8","tagPath":"/content/cq:tags/snowflake-site/taxonomy/solution-center/certification/community-sourced","tagIcon":""},"isDeveloperGuidesPage":false,":type":"snowflake-site/components/quickstart/quickstart-hero","fragmentPath":"/content/dam/snowflake-site/en/content-fragments/quickstarts/data-engineering-with-notebooks"},"flexible_column_cont":{"id":"flexible-column-container-6d65531dda","propertiesId":"quickstart-template-main-flexible-container","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-74645e2b3d",":items":{"contentfragment":{"id":"contentfragment-90c5d7317d","description":"Build data engineering pipelines using Snowflake Notebooks with Python and SQL for interactive, collaborative pipeline development.","paragraphs":["<!-- ------------------------ -->\n","\u003Ch2\u003EOverview\u003C/h2\u003E\n","\u003Cp\u003ENotebooks are a very popular tool that are used to do everything from ad-hoc exploration of data to productionalized data engineering pipelines. While Notebooks can contain a mix of both Python and SQL, most of the time they're used for Python coding. In my previous Quickstart I detailed \u003Ca href=\"/en/developers/guides/data-engineering-pipelines-with-snowpark-python/\"\u003Ehow to build Python data engineering pipelines in Snowflake\u003C/a\u003E using Visual Studio Code, from a lower-level developer perspective.\u003C/p\u003E\n","\u003Cp\u003EThis Quickstart will focus on how to build Python data engineering pipelines using Snowflake native Notebooks! Additionally, it will provide all the details needed to manage and deploy those Notebooks through an automated CI/CD pipeline from development to production! Here's a quick visual overview of what we'll accomplish in this Quickstart:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EWhat You’ll Learn\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to ingest custom file formats (like Excel) with Snowpark from an external stage (such as an S3 bucket) into a Snowflake table\u003C/li\u003E\u003Cli\u003EHow to access data from Snowflake Marketplace and use it for your analysis\u003C/li\u003E\u003Cli\u003EHow to use Snowflake Notebooks and the Snowpark DataFrame API to build data engineering pipelines\u003C/li\u003E\u003Cli\u003EHow to add logging to your Python data engineering code and monitor from within Snowsight\u003C/li\u003E\u003Cli\u003EHow to use the Snowflake Python Management API to programmatically work with Snowflake objects\u003C/li\u003E\u003Cli\u003EHow to use the Python Task DAG API to programmatically manage Snowflake Tasks\u003C/li\u003E\u003Cli\u003EHow to use Cortex Code to accelerate data engineering development directly in Snowsight\u003C/li\u003E\u003Cli\u003EHow to build CI/CD pipelines using Snowflake's Git Integration, the Snowflake CLI, and GitHub Actions\u003C/li\u003E\u003Cli\u003EHow to deploy Snowflake Notebooks from dev to production\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You'll Build\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EA data share from the Snowflake Marketplace to access weather data\u003C/li\u003E\u003Cli\u003EA data engineering pipeline with a Notebook to ingest Excel files into Snowflake\u003C/li\u003E\u003Cli\u003EA data engineering pipeline with a Notebook to transform and aggregate data\u003C/li\u003E\u003Cli\u003EA DAG (or Directed Acyclic Graph) of Tasks to orchestrate/schedule the pipelines\u003C/li\u003E\u003Cli\u003EA CI/CD pipeline to deploy the Notebooks to production\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EPrerequisites\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EFamiliarity with Python\u003C/li\u003E\u003Cli\u003EFamiliarity with the DataFrame API\u003C/li\u003E\u003Cli\u003EFamiliarity with Snowflake\u003C/li\u003E\u003Cli\u003EFamiliarity with Git repositories and GitHub\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003EWhat You’ll Need\u003C/h3\u003E\n","\u003Cp\u003EYou will need the following things before beginning:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ESnowflake account\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EA Snowflake Account\u003C/strong\u003E. Visit the \u003Ca href=\"https://app.snowflake.com/\"\u003ESnowflake Account Sign In\u003C/a\u003E page to log into your account or to sign up for a trial account (we recommend Enterprise).\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EA Snowflake user created with ACCOUNTADMIN permissions\u003C/strong\u003E. This user will be used to get things setup in Snowflake.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003EGitHub account\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EA GitHub account\u003C/strong\u003E. If you don't already have a GitHub account you can create one for free. Visit the \u003Ca href=\"https://github.com/signup\"\u003EJoin GitHub\u003C/a\u003E page to get started.\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EQuickstart Setup\u003C/h2\u003E\n","\u003Ch3\u003ECreate a GitHub Personal Access Token\u003C/h3\u003E\n","\u003Cp\u003EIn order for Snowflake to authenticate to your GitHub repository, you will need to generate a personal access token. Please follow the \u003Ca href=\"https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens#creating-a-personal-access-token-classic\"\u003ECreating a personal access token\u003C/a\u003E instructions to create your token.\u003C/p\u003E\n","\u003Cp\u003EMake sure to save the token before leaving the page, as we will be using it a couple of times during this Quickstart.\u003C/p\u003E\n","\u003Ch3\u003EFork the Quickstart Repository\u003C/h3\u003E\n","\u003Cp\u003EYou'll need to create a fork of the repository for this Quickstart in your GitHub account. Visit the \u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-data-engineering-with-notebooks\"\u003EData Engineering with Snowflake Notebooks associated GitHub Repository\u003C/a\u003E and click on the "Fork" button near the top right. Complete any required fields and click "Create Fork".\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ESetup Snowflake\u003C/h2\u003E\n","\u003Cp\u003EIn this section we're going to set up the required objects in Snowflake to use notebooks in Workspaces and have that Workspace connected directly to our forked Git repository.\u003C/p\u003E\n","\u003Ch3\u003ECreate GitHub API Integration\u003C/h3\u003E\n","\u003Cp\u003ETo connect a Workspace to your GitHub repository, you'll need to create an API integration that allows Snowflake to communicate with GitHub. In your Snowflake environment, run the following in a SQL script in your default Workspace:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE ACCOUNTADMIN;\n\nCREATE OR REPLACE API INTEGRATION GITHUB_API_INTEGRATION\n    API_PROVIDER = GIT_HTTPS_API\n    API_ALLOWED_PREFIXES = ('https://github.com/')\n    ALLOWED_AUTHENTICATION_SECRETS = ALL\n    ENABLED = TRUE;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis API integration allows Snowflake to access GitHub repositories. The \u003Ccode\u003EALLOWED_AUTHENTICATION_SECRETS = ALL\u003C/code\u003E setting allows the integration to use any secret for authentication, which we'll need for private repositories or to push changes back to GitHub.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E: Only users with ACCOUNTADMIN privileges (or the CREATE INTEGRATION privilege) can create API integrations. If you don't have these privileges, ask your Snowflake administrator to create this integration for you.\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E: If you'd rather authenticate to GitHub using OAuth, instead of PAT, follow the steps in \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/git/git-setting-up-public#configure-for-authenticating-with-oauth\"\u003EConfigure for authenticating with OAuth\u003C/a\u003E and use that \u003Ccode\u003ECREATE OR REPLACE API INTEGRATION\u003C/code\u003E statement instead.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ECreate Workspace\u003C/h3\u003E\n","\u003Cp\u003ENow let's create a Git-integrated workspace connected to your forked repository. Workspaces provide a unified development environment where you can create, organize, and manage notebooks and other code files. Git-integrated workspaces allow you to sync your work with a Git repository for version control and collaboration.\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the left navigation menu, select \u003Cstrong\u003EProjects → Workspaces\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the Workspaces menu at the top left, under "+", select \u003Cstrong\u003EGit workspace\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EIn the "Create Workspace" dialog:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ERepository URL\u003C/strong\u003E: Paste the URL of your forked repository (e.g., \u003Ccode\u003Ehttps://github.com/YOUR_USERNAME/sfguide-data-engineering-with-notebooks\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EWorkspace name\u003C/strong\u003E: Leave it as-is, or enter a name you prefer (e.g., \u003Ccode\u003Esfguide-data-engineering-with-notebooks\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAPI Integration\u003C/strong\u003E: Select the \u003Ccode\u003EGITHUB_API_INTEGRATION\u003C/code\u003E we created from the dropdown\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EAuthentication method\u003C/strong\u003E: Select \u003Ccode\u003EPersonal access token\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ECredentials secret\u003C/strong\u003E: Select your "USER$<username>" database and the "PUBLIC" schema\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EFor authentication, select \u003Cstrong\u003EPersonal access token\u003C/strong\u003E and then click \u003Cstrong\u003E+ Secret\u003C/strong\u003E to create a new secret with your GitHub Personal Access Token\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003EClick \u003Cstrong\u003ECreate\u003C/strong\u003E\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ESnowflake will now clone the repository and create your workspace. This may take a few moments. Once complete, you'll see all the files from the GitHub repository in the left pane of your workspace. You can now open these files directly within Snowflake.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E - The Workspace provides a Jupyter-compatible notebook experience with direct access to governed Snowflake data. Notebooks run in a pre-built container environment optimized for AI/ML development with fully-managed access to CPUs and GPUs.\u003C/p\u003E\n\u003C/blockquote\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E: If you'd rather authenticate to GitHub using OAuth, instead of PAT, select \u003Ccode\u003EOAuth2\u003C/code\u003E instead of \u003Ccode\u003EPersonal access token\u003C/code\u003E in "Authentication method" and follow the steps for OAuth2 authentication in \u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git#create-a-git-workspace\"\u003ECreate a Git workspace\u003C/a\u003E.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ECreate Demo Objects in Snowflake\u003C/h3\u003E\n","\u003Cp\u003ENext we will create the Snowflake objects used during this Guide. To do that we will run a SQL script from our new Workspace:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn your Workspace, in the left "Files" pane, open the file \u003Ccode\u003Escripts/setup.sql\u003C/code\u003E\u003C/li\u003E\u003Cli\u003ERun all of the SQL statements in this script by clicking on the blue down arrow and "Run all", next to play button at the top of the script, or using the shortcut CMD/CTRL+Shift+Enter\u003C/li\u003E\u003C/ol\u003E\n","\u003Ch3\u003ECreate and Switch to Dev Branch\u003C/h3\u003E\n","\u003Cp\u003EDuring this Quickstart we will do our development work in a \u003Ccode\u003Edev\u003C/code\u003E branch of the repository. One of the great features of Git-integrated Workspaces is the ability to create and manage branches directly within Snowsight.\u003C/p\u003E\n","\u003Cp\u003ELet's create the \u003Ccode\u003Edev\u003C/code\u003E branch now:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn your Workspace, look at the top of the file explorer pane on the left\u003C/li\u003E\u003Cli\u003EClick on the \u003Cstrong\u003EChanges\u003C/strong\u003E tab to open the Git panel\u003C/li\u003E\u003Cli\u003EYou'll see the current branch displayed (likely \u003Ccode\u003Emain\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003EClick on the branch dropdown to open the branch selector\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003E+ New\u003C/strong\u003E to create a new branch\u003C/li\u003E\u003Cli\u003EEnter "dev" (all lowercase) as the branch name and click \u003Cstrong\u003ECreate\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EYour new \u003Ccode\u003Edev\u003C/code\u003E branch will be created and you'll automatically be switched to it. You can verify this by looking at the branch name displayed in the Changes panel.\u003C/p\u003E\n","\u003Cp\u003EOnce you're on the \u003Ccode\u003Edev\u003C/code\u003E branch, you're ready to start running the setup cells.\u003C/p\u003E\n","\u003Ch3\u003ECreate the Notebook Service\u003C/h3\u003E\n","\u003Cp\u003ENotebooks in Workspaces run on Snowpark Container Services (SPCS) compute pools rather than traditional warehouses. A compute pool in Snowflake is a collection of virtual machine (VM) nodes that run containerized workloads. Snowflake provides a default system compute pool, which is available to all accounts, that we will use for this Quickstart, named \u003Ccode\u003ESYSTEM_COMPUTE_POOL_CPU\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EBut before you can run notebooks interactively, you need to create a notebook service in the default system compute pool. A notebook service is a Snowflake-managed container service that hosts the notebook kernel and executes your code. Each notebook service is scoped to a single user and can be shared by multiple notebooks.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E - Notebook services can currently only be created through the Workspaces UI, not via SQL.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003ETo create your notebook service:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn your Workspace, open the \u003Ccode\u003E00_start_here.ipynb\u003C/code\u003E Notebook\u003C/li\u003E\u003Cli\u003EClick the \u003Cstrong\u003EConnect\u003C/strong\u003E button at the top of the notebook\u003C/li\u003E\u003Cli\u003EEnter the following values in the "Connect your notebook" dialog (and expand "Service settings"):\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EService name\u003C/strong\u003E: Enter \u003Ccode\u003ENOTEBOOK_SERVICE\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EArtifact repositories (optional)\u003C/strong\u003E: Select \u003Ccode\u003ESNOWFLAKE.SNOWPARK.PYPI_SHARED_REPOSITORY\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EService settings\u003C/strong\u003E:\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ECompute type\u003C/strong\u003E: Leave with default of \u003Ccode\u003ECPU\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EPython version\u003C/strong\u003E: Leave with default\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ERuntime version\u003C/strong\u003E: Leave with default\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ECompute pool\u003C/strong\u003E: Select \u003Ccode\u003ESYSTEM_COMPUTE_POOL_CPU\u003C/code\u003E\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EIdle timeout\u003C/strong\u003E: Select \u003Ccode\u003E1 hour\u003C/code\u003E\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003EClick \u003Cstrong\u003ECreate and connect\u003C/strong\u003E\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EThe notebook service will start up, which may take a minute or two for the first time. Once connected, you'll see a green "Connected" indicator.\u003C/p\u003E\n","\u003Cp\u003EThe Snowflake Artifact Repository allows you to install third-party packages in your notebooks. And in this case we're using Snowflake’s default PyPI Artifact Repository to install PyPI packages. Check out \u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-artifact-repositories\"\u003EUsing artifact repositories\u003C/a\u003E for more details.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETip\u003C/strong\u003E - Since notebook services can be shared across multiple notebooks, you only need to create one service. When you open other notebooks in your workspace, you can connect them to the same \u003Ccode\u003ENOTEBOOK_SERVICE\u003C/code\u003E to share compute resources.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ELoad Weather\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be "loading" the raw weather data to Snowflake. But "loading" is really the wrong word here. Because we're using Snowflake's unique data sharing capability we don't actually need to copy the data to our Snowflake account with a custom ETL process. Instead we can directly access the weather data shared by Pelmorex Weather Source in the Snowflake Marketplace. To put this in context, we are on step \u003Cstrong\u003E#2\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ELoad Weather Data from Snowflake Marketplace\u003C/h3\u003E\n","\u003Cp\u003EPelmorex Weather Source is a leading provider of global weather and climate data and their OnPoint Product Suite provides businesses with the necessary weather and climate data to quickly generate meaningful and actionable insights for a wide range of use cases across industries. Let's connect to the \u003Ccode\u003EPelmorex Weather Source: Frostbyte\u003C/code\u003E feed in the Snowflake Marketplace by following these steps:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003ELogin to Snowsight\u003C/li\u003E\u003Cli\u003EClick on the \u003Ccode\u003EMarketplace\u003C/code\u003E -> \u003Ccode\u003ESnowflake Marketplace\u003C/code\u003E link in the left navigation bar\u003C/li\u003E\u003Cli\u003EEnter "Pelmorex Weather Source: Frostbyte" in the search box and click return\u003C/li\u003E\u003Cli\u003EClick on the "Pelmorex Weather Source: Frostbyte" listing tile\u003C/li\u003E\u003Cli\u003EClick the blue "Get" button\n\u003Cul\u003E\u003Cli\u003EExpand the "Options" dialog\u003C/li\u003E\u003Cli\u003EChange the "Database name" to read "FROSTBYTE_WEATHERSOURCE" (all capital letters)\u003C/li\u003E\u003Cli\u003ESelect the "DEMO_ROLE" role to have access to the new database\u003C/li\u003E\u003C/ul\u003E\n\u003C/li\u003E\u003Cli\u003EClick on the blue "Get" button\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThat's it... we don't have to do anything from here to keep this data updated. The provider will do that for us and data sharing means we are always seeing whatever they have published. How amazing is that? Just think of all the things you didn't have do here to get access to an always up-to-date, third-party dataset!\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ELoad Excel Files\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be loading data from two Excel files in S3 into the \u003Ccode\u003ELOCATION\u003C/code\u003E and \u003Ccode\u003EORDER_DETAIL\u003C/code\u003E tables. To do this we'll take advantage of the \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-sprocs#reading-dynamically-specified-files-with-snowflakefile\"\u003ESnowpark Python file access feature\u003C/a\u003E. For more details on this please see my related blog post \u003Ca href=\"https://medium.com/snowflake/simplify-data-ingestion-with-snowpark-python-file-access-f2bc0e4cd887\"\u003ESimplify data ingestion with Snowpark Python file access\u003C/a\u003E.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E - Workspace Notebooks do not yet support \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/build_scoped_file_url\"\u003EScoped URLs\u003C/a\u003E or \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/build_stage_file_url\"\u003EStage URLs\u003C/a\u003E. So as a workaround for now we will copy the Excel files from the external stage to a temporary internal stage and open from there. This note was last updated on 2/11/26.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003ETo put this in context, we are on step \u003Cstrong\u003E#3\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ERun the Notebook\u003C/h3\u003E\n","\u003Cp\u003EIn Workspaces, open the \u003Ccode\u003E01_load_excel_files\u003C/code\u003E notebook,  click on the "Run all" button near the top right of the window. This will execute all cells in the notebook, in order.\u003C/p\u003E\n","\u003Ch3\u003ENotebook Git Integration\u003C/h3\u003E\n","\u003Cp\u003EYou will notice that to the left of the main Notebook area there is a sidebar which shows the files in the Workspace. The two notebooks that we'll be running and deploying in this Quickstart can be found in the \u003Ccode\u003E/notebooks\u003C/code\u003E folder. Above the file viewer you will see a \u003Cstrong\u003EChanges\u003C/strong\u003E button/tab which contains the Git related controls that are built into Workspaces. Here you are able to work with branches, push and pull changes, and view diffs. Here's a screenshot:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_notebook_git.png?v=df037233\" alt=\"assets/snowsight_notebook_git.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ENotebook Cell References\u003C/h3\u003E\n","\u003Cp\u003EWorkspace Notebooks provide powerful interoperability between SQL and Python cells. You can easily pass data between cells using standard Jupyter patterns.\u003C/p\u003E\n","\u003Cp\u003EFor example, you can run a SQL query in one cell and then use the results in a Python cell. The results of SQL cells are automatically available as DataFrames. Here's an example:\u003C/p\u003E\n","\u003Cp\u003EIn the \u003Ccode\u003Esql_get_spreadsheets\u003C/code\u003E SQL cell we have:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESELECT '@INTEGRATIONS.FROSTBYTE_RAW_STAGE/intro/order_detail.xlsx' AS STAGE_FILE_PATH, 'order_detail' AS WORKSHEET_NAME, 'ORDER_DETAIL' AS TARGET_TABLE\nUNION\nSELECT '@INTEGRATIONS.FROSTBYTE_RAW_STAGE/intro/location.xlsx', 'location', 'LOCATION';\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd then in the subsequent \u003Ccode\u003Epy_process_spreadsheets\u003C/code\u003E Python cell we can access the prior result like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E# Process each file from the sql_get_spreadsheets cell above\nfiles_to_load = dataframe_1\nfor index, excel_file in files_to_load.iterrows():\n    print(f"Processing Excel file {excel_file['STAGE_FILE_PATH']}")\n    load_excel_worksheet_to_table(session, excel_file['STAGE_FILE_PATH'], excel_file['WORKSHEET_NAME'], excel_file['TARGET_TABLE'])\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFor more details, please see the \u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-edit-run\"\u003ENotebooks in Workspaces documentation\u003C/a\u003E for information on cell references.\u003C/p\u003E\n","\u003Ch3\u003EDynamic File Access\u003C/h3\u003E\n","\u003Cp\u003ELike I mentioned at the beginning of this section, we're able to read and process Excel files with the \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-sprocs#reading-dynamically-specified-files-with-snowflakefile\"\u003ESnowpark Python file access feature\u003C/a\u003E. And this same principle applies to more than just Excel files, you can use it to process any file format you'd like. For more details on this please see my related blog post \u003Ca href=\"https://medium.com/snowflake/simplify-data-ingestion-with-snowpark-python-file-access-f2bc0e4cd887\"\u003ESimplify data ingestion with Snowpark Python file access\u003C/a\u003E.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E - Workspace Notebooks do not yet support \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/build_scoped_file_url\"\u003EScoped URLs\u003C/a\u003E or \u003Ca href=\"https://docs.snowflake.com/en/sql-reference/functions/build_stage_file_url\"\u003EStage URLs\u003C/a\u003E. So as a workaround for now we will copy the Excel files from the external stage to a temporary internal stage and open from there. This note was last updated on 2/11/26.\u003C/p\u003E\n\u003C/blockquote\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ELoad Daily City Metrics\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be joining data from our \u003Ccode\u003ELOCATION\u003C/code\u003E and \u003Ccode\u003EORDER_DETAIL\u003C/code\u003E tables (from the previous step) with the weather data we set up in step 2 to produce an aggregated reporting table \u003Ccode\u003EDAILY_CITY_METRICS\u003C/code\u003E. We'll leverage the Snowpark DataFrame API to perform the data transformations, and will also show how to incorporate logging into your code. To put this in context, we are on step \u003Cstrong\u003E#4\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ERun the Notebook\u003C/h3\u003E\n","\u003Cp\u003EOpen the \u003Ccode\u003E02_load_daily_city_metrics\u003C/code\u003E Notebook click on the "Run all" button near the top right of the window. This will execute all cells in the notebook, in order.\u003C/p\u003E\n","\u003Ch3\u003ESnowpark DataFrame API\u003C/h3\u003E\n","\u003Cp\u003EIn this step we're starting to really use the Snowpark DataFrame API for data transformations. The Snowpark API provides the same functionality as the \u003Ca href=\"https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/index.html\"\u003ESpark SQL API\u003C/a\u003E. To begin with you need to create a Snowpark session object. Like in PySpark, this can be accomplished with the \u003Ccode\u003ESession.builder.configs().create()\u003C/code\u003E methods. But within a Snowflake Notebook this is simplified and can be accomplished with just \u003Ccode\u003Esession = get_active_session()\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EOnce you have a Snowpark session you can begin working with data. In this Notebook we're using DataFrames to join the data from different tables into an \u003Ccode\u003Eorder_detail\u003C/code\u003E DataFrame using the \u003Ccode\u003Ejoin()\u003C/code\u003E API.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Eorder_detail = order_detail.join(location, order_detail['LOCATION_ID'] == location['LOCATION_ID'])\norder_detail = order_detail.join(history_day, (F.builtin("DATE")(order_detail['ORDER_TS']) == history_day['DATE_VALID_STD']) & (location['ISO_COUNTRY_CODE'] == history_day['COUNTRY']) & (location['CITY'] == history_day['CITY_NAME']))\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAfter that we're then aggregating the DataFrame using APIs such as \u003Ccode\u003Eagg()\u003C/code\u003E, \u003Ccode\u003Egroup_by()\u003C/code\u003E, and \u003Ccode\u003Eselect()\u003C/code\u003E.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Efinal_agg = order_detail.group_by(F.col('DATE_VALID_STD'), F.col('CITY_NAME'), F.col('ISO_COUNTRY_CODE')) \\\n                        .agg( \\\n                            F.sum('PRICE').alias('DAILY_SALES_SUM'), \\\n                            F.avg('AVG_TEMPERATURE_AIR_2M_F').alias("AVG_TEMPERATURE_F"), \\\n                            F.avg("TOT_PRECIPITATION_IN").alias("AVG_PRECIPITATION_IN"), \\\n                        ) \\\n                        .select(F.col("DATE_VALID_STD").alias("DATE"), F.col("CITY_NAME"), F.col("ISO_COUNTRY_CODE").alias("COUNTRY_DESC"), \\\n                            F.builtin("ZEROIFNULL")(F.col("DAILY_SALES_SUM")).alias("DAILY_SALES"), \\\n                            F.round(F.col("AVG_TEMPERATURE_F"), 2).alias("AVG_TEMPERATURE_FAHRENHEIT"), \\\n                            F.round(F.col("AVG_PRECIPITATION_IN"), 2).alias("AVG_PRECIPITATION_INCHES"), \\\n                        )\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd finally if the target table exists we're using the \u003Ccode\u003Emerge()\u003C/code\u003E DataFrame API to perform an Upsert operation on the target table. This is what enables us to perform incremental processing.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E    dcm.merge(final_agg, (dcm['DATE'] == final_agg['DATE']) & (dcm['CITY_NAME'] == final_agg['CITY_NAME']) & (dcm['COUNTRY_DESC'] == final_agg['COUNTRY_DESC']), \\\n                        [F.when_matched().update(cols_to_update), F.when_not_matched().insert(cols_to_update)])\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EFor more details about the Snowpark Python DataFrame API, please check out our \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowpark/python/working-with-dataframes.html\"\u003EWorking with Dataframe in Snowpark Python\u003C/a\u003E page.\u003C/p\u003E\n","\u003Ch3\u003EPython Management API\u003C/h3\u003E\n","\u003Cp\u003EThe new Python Management API allows us to programmatically interact with Snowflake with native Python objects. This API can be used to both inspect and manage Snowflake objects. In the previous Quickstart we checked for the existence of an object by using SQL like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003Edef table_exists(session, database_name='', schema_name='', table_name=''):\n    exists = session.sql("SELECT EXISTS (SELECT * FROM {}.INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA = '{}' AND TABLE_NAME = '{}') AS TABLE_EXISTS".format(database_name, schema_name, table_name)).collect()[0]['TABLE_EXISTS']\n    return exists\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EBut with the Python Management API this can now be done with native Python objects like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Edef table_exists(session, database_name='', schema_name='', table_name=''):\n    root = Root(session)\n    tables = root.databases[database_name].schemas[schema_name].tables.iter(like=table_name)\n    for table_obj in tables:\n        if table_obj.name == table_name:\n            return True\n\n    return False\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd this is really just the beginning of what you can do with this new library. Please check out the \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview\"\u003ESnowflake Python Management API\u003C/a\u003E documentation for more details.\u003C/p\u003E\n","\u003Ch3\u003ELogging in Python\u003C/h3\u003E\n","\u003Cp\u003EA key aspect of building robust data engineering pipelines involves instrumenting our code. This enables the monitoring and operations of our code, and is especially important when automating the deployment and monitoring of our pipelines with DevOps. Snowflake has a rich set of \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/logging-tracing/logging-tracing-overview\"\u003ELogging and Tracing\u003C/a\u003E capabilities to help.\u003C/p\u003E\n","\u003Cp\u003EYou'll notice that in the \u003Ccode\u003Epy_initialize\u003C/code\u003E cell of this Notebook we're using Snowflake's logging capabilities. There are two steps to do so in your code. The first is to create a logger to use:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Elogger_name = 'demo_logger'\nlogger = logging.getLogger(logger_name)\nlogger.setLevel(logging.INFO)\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EAnd the second is to actually log debugging and informational messages at the appropriate places in your code:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003Elogger.info(f"Begin executing notebook {notebook_name}", extra = {'logger_name': logger_name})\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIn addition to custom logging, Snowflake is instrumenting all services/features to take advantage of logging and tracing as well. For example, when you ran this Notebook earlier it logged a number of messages by default, like when each cell executed.\u003C/p\u003E\n","\u003Cp\u003EAll of your log messages can be found in your default logging table, which we created in step 1. If you look back at the code from step 1 you'll find that we created an event table named \u003Ccode\u003EDEMO_DB.INTEGRATIONS.DEMO_EVENTS\u003C/code\u003E and then set that as the default event table for the account. You can now use this table just like any other table in Snowflake to query and act on the log data.\u003C/p\u003E\n","\u003Cp\u003ELet's view the logs that have been created so far by running the query in Step 04 of the \u003Ccode\u003E00_start_here\u003C/code\u003E Notebook. Here's the query to do that:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003ESELECT \n    TIMESTAMP,\n    VALUE AS LOG_MESSAGE,\n    RESOURCE_ATTRIBUTES:"snow.service.name"::string AS SERVICE_NAME,\n    RECORD_ATTRIBUTES:"severity_text"::string AS SEVERITY\nFROM DEMO_DB.INTEGRATIONS.DEMO_EVENTS\nWHERE RECORD_TYPE = 'LOG'\n--  AND RESOURCE_ATTRIBUTES:"snow.service.name" = 'NOTEBOOK_SERVICE'\n  AND TIMESTAMP > DATEADD(hour, -1, CURRENT_TIMESTAMP())\nORDER BY TIMESTAMP DESC\nLIMIT 100;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EUsing Cortex Code\u003C/h2\u003E\n","\u003Cp\u003ENow that we've built our data engineering pipelines, let's look at a tool that can help accelerate your development workflow significantly. \u003Ca href=\"https://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight\"\u003ECortex Code\u003C/a\u003E is an AI-powered coding assistant built directly into Snowsight that understands your Snowflake environment, including SQL worksheets, dbt Projects, and Notebooks. It can generate and modify code, explain existing logic, and even run notebooks — all from a conversational interface without ever leaving Snowsight.\u003C/p\u003E\n","\u003Cp\u003EFor data engineers, this is a game changer. Instead of manually writing your Python DataFrame (or SQL) queries, you can describe what you want in plain English and Cortex Code will generate context-aware code that follows Snowflake best practices. Whether you're building a new transformation, adding a debugging query, or exploring unfamiliar data, Cortex Code helps you move faster while staying in your flow.\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ENote\u003C/strong\u003E - Cortex Code requires the \u003Ccode\u003ESNOWFLAKE.COPILOT_USER\u003C/code\u003E database role and either the \u003Ccode\u003ESNOWFLAKE.CORTEX_USER\u003C/code\u003E or \u003Ccode\u003ESNOWFLAKE.CORTEX_AGENT_USER\u003C/code\u003E database role. It also requires \u003Ca href=\"https://docs.snowflake.com/en/user-guide/snowflake-cortex/cross-region-inference\"\u003ECross-region inference\u003C/a\u003E to be enabled. See the \u003Ca href=\"https://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight\"\u003ECortex Code documentation\u003C/a\u003E for full details.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003ECortex Code in Action\u003C/h3\u003E\n","\u003Cp\u003ELet's see Cortex Code in action with the Notebook we just ran. Open the \u003Ccode\u003E02_load_daily_city_metrics\u003C/code\u003E Notebook in your Workspace and then follow these steps:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EClick the Cortex Code icon in the lower-right corner of the Workspace to open the assistant panel\u003C/li\u003E\u003Cli\u003EIn the message box, enter the following prompt and press Enter:\u003C/li\u003E\u003C/ol\u003E\n\u003Cpre\u003E\u003Ccode\u003EAdd a Python cell under the debugging section that uses Snowpark DataFrame to query the DAILY_CITY_METRICS table and show the top 10 cities by total sales, including total days and average temperature.\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003ECortex Code will analyze the context of your Notebook and generate a new Python cell with the appropriate Snowpark DataFrame code. You'll be able to review the suggested change before applying it. Once you're happy with it, apply the change and run the new cell to see the results.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/cortex_code_snowsight.png?v=df037233\" alt=\"assets/cortex_code_snowsight.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EWhile this was just a simple debugging cell, we can leverage Cortex Code to write any part (or all) of our pipelines for us! As you continue building out your data engineering pipelines, Cortex Code can help you iterate faster — from prototyping new transformations to troubleshooting issues in production.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EDeploy Notebook Project to Dev\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be deploying the dev versions of our two data engineering Notebooks: \u003Ccode\u003E01_load_excel_files\u003C/code\u003E and \u003Ccode\u003E02_load_daily_city_metrics\u003C/code\u003E. To deploy notebooks to Snowflake we will create a \u003Ccode\u003ENOTEBOOK PROJECT\u003C/code\u003E object in our \u003Ccode\u003EDEV_SCHEMA\u003C/code\u003E, along with the other resources in our development environment.\u003C/p\u003E\n","\u003Cp\u003ETo put this in context, we are on step \u003Cstrong\u003E#5\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ENOTEBOOK PROJECT Object\u003C/h3\u003E\n","\u003Cp\u003ENotebook Project Objects (NPOs) are the key to deploying and scheduling notebooks in production with Workspace Notebooks. An NPO is a schema-level object that encapsulates your notebook files and their dependencies, making them ready for scheduled execution.\u003C/p\u003E\n","\u003Cp\u003EKey characteristics of NPOs:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003ESchema-level object\u003C/strong\u003E: NPOs exist within a specific schema (\u003Ccode\u003Edatabase_name.schema_name.npo_name\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EEncapsulation\u003C/strong\u003E: An NPO captures all notebook files from your workspace, ensuring all dependencies are available during execution\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EVersioning\u003C/strong\u003E: NPOs support versioned deployments, allowing you to track changes and roll back if needed\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EExecution\u003C/strong\u003E: You execute an NPO using the \u003Ccode\u003EEXECUTE NOTEBOOK PROJECT\u003C/code\u003E command, specifying which notebook file to run with the \u003Ccode\u003EMAIN_FILE\u003C/code\u003E parameter\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EThe NPO deployment model provides a clean separation between interactive development (in Workspaces) and production execution (via NPOs and Tasks). This ensures that your scheduled notebooks run exactly the code that was deployed, not whatever is currently in your workspace.\u003C/p\u003E\n","\u003Ch3\u003EDeploy Notebooks\u003C/h3\u003E\n","\u003Cp\u003ETo deploy the dev versions of our notebooks, we'll create an NPO using a simple Python script. The \u003Ccode\u003Escripts/deploy_notebooks.py\u003C/code\u003E script handles the deployment by:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EGetting a temporary stage from the Snowpark session\u003C/li\u003E\u003Cli\u003EUploading all notebook files from the local folder to the stage\u003C/li\u003E\u003Cli\u003ECreating or updating the Notebook Project Object from the staged files\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ERun the deployment cell in the \u003Ccode\u003E00_start_here\u003C/code\u003E Notebook to deploy the notebooks. The cell uses the \u003Ccode\u003E%run\u003C/code\u003E magic to execute the deployment script:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E%run scripts/deploy_notebooks.py DEMO_DB DEV_SCHEMA DEMO_PIPELINES_NP ./notebooks\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EThis command deploys all notebooks from the \u003Ccode\u003E./notebooks\u003C/code\u003E folder to a Notebook Project Object named \u003Ccode\u003EDEMO_PIPELINES_NP\u003C/code\u003E in \u003Ccode\u003EDEMO_DB.DEV_SCHEMA\u003C/code\u003E.\u003C/p\u003E\n","\u003Cp\u003EYou can verify the deployment by running:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003ESHOW NOTEBOOK PROJECTS IN DEMO_DB.DEV_SCHEMA;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EOnce deployed, you'll be able to execute these notebooks on a schedule using Snowflake Tasks.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EOrchestrate Pipelines\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be orchestrating our new Snowpark Notebook pipelines with Snowflake's native orchestration feature named Tasks. You can create and deploy Snowflake Task objects using SQL as well as with our Python Task APIs. For this Quickstart, we will use Snowflake Python Task APIs to create the Tasks. We will create two tasks, one for each Notebook, and chain them together. To put this in context, we are on step \u003Cstrong\u003E#6\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EDeploy Task DAG\u003C/h3\u003E\n","\u003Cp\u003EToggle back to the \u003Ccode\u003E00_start_here\u003C/code\u003E Notebook, scroll down to the "Step 06 Orchestrate Pipelines" section, and run each of the cells.\u003C/p\u003E\n","\u003Ch3\u003EPython Task DAG API\u003C/h3\u003E\n","\u003Cp\u003EIn this step we will create a DAG (or Directed Acyclic Graph) of Tasks using the new \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview\"\u003ESnowflake Python Management API\u003C/a\u003E. The Task DAG API builds upon the Python Management API to provide advanced Task management capabilities. And if you've used Airflow before, this Python API should look familiar as it's similar to the Airflow v1 Python API. For more details see \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-managing-tasks\"\u003EManaging Snowflake tasks and task graphs with Python\u003C/a\u003E.\u003C/p\u003E\n","\u003Cp\u003EHere is the key part of the code:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-python\"\u003E# Define the DAG\nwith DAG(dag_name, schedule=timedelta(days=1), warehouse=warehouse_name) as dag:\n    dag_task1 = DAGTask("LOAD_EXCEL_FILES_TASK", definition=f'''\n        EXECUTE NOTEBOOK PROJECT {database_name}.{schema_name}.{notebook_project_name}\n            MAIN_FILE = '01_load_excel_files.ipynb'\n            COMPUTE_POOL = {compute_pool}\n            RUNTIME = '{runtime}'\n            QUERY_WAREHOUSE = {warehouse_name}\n            ARTIFACT_REPOSITORIES = ({artifact_repository})\n            ARGUMENTS = '--database-name {database_name} --schema-name {schema_name}'\n        ''', warehouse=warehouse_name)\n    dag_task2 = DAGTask("LOAD_DAILY_CITY_METRICS", definition=f'''\n        EXECUTE NOTEBOOK PROJECT {database_name}.{schema_name}.{notebook_project_name}\n            MAIN_FILE = '02_load_daily_city_metrics.ipynb'\n            COMPUTE_POOL = {compute_pool}\n            RUNTIME = '{runtime}'\n            QUERY_WAREHOUSE = {warehouse_name}\n            ARGUMENTS = '--database-name {database_name} --schema-name {schema_name}'\n        ''', warehouse=warehouse_name)\n\n    # Define the dependencies between the tasks\n    dag_task1 >> dag_task2 # dag_task1 is a predecessor of dag_task2\n\n# Create the DAG in Snowflake\ndag_op.deploy(dag, mode="orreplace")\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EYou can see that we're defining two tasks, one for each Notebook, and that each task calls \u003Ccode\u003EEXECUTE NOTEBOOK PROJECT\u003C/code\u003E for the corresponding Notebook in our NPO. The key parameters are:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EMAIN_FILE\u003C/strong\u003E: The notebook file to execute within the NPO\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ECOMPUTE_POOL\u003C/strong\u003E: The SPCS compute pool to run the notebook on\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003ERUNTIME\u003C/strong\u003E: The container runtime version (e.g., \u003Ccode\u003EV2.5-CPU-PY3.12\u003C/code\u003E)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EQUERY_WAREHOUSE\u003C/strong\u003E: The warehouse to use for SQL queries\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EWe then define the dependencies and deploy the DAG. As you can see this makes managing complex Task DAGs much easier!\u003C/p\u003E\n","\u003Cp\u003EThis code is also available in the \u003Ccode\u003Escripts/deploy_task_dag.py\u003C/code\u003E script which could be used to automate the Task DAG deployment further.\u003C/p\u003E\n","\u003Ch3\u003ETask Viewer in Snowsight\u003C/h3\u003E\n","\u003Cp\u003ENow, after your DAG is deployed, all the tasks in your DAG will be running as per the defined schedule. However, as a Snowflake user, how can you peek into the success and failure of each run, look at the task run time, and more?\u003C/p\u003E\n","\u003Cp\u003ESnowflake provides some rich task observability features in the Snowsight UI. Try it out for yourself by following these steps:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn the Snowsight left navigation menu, click \u003Cstrong\u003ECatalog\u003C/strong\u003E » \u003Cstrong\u003EDatabase Explorer\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003EIn the "Database Explorer" pane, navigate to the \u003Ccode\u003EDEMO_DB\u003C/code\u003E database and \u003Ccode\u003EDEV_SCHEMA\u003C/code\u003E schema.\u003C/li\u003E\u003Cli\u003EFor the selected schema, select and expand \u003Cstrong\u003ETasks\u003C/strong\u003E.\u003C/li\u003E\u003Cli\u003ESelect the \u003Ccode\u003EDEMO_DAG\u003C/code\u003E task. Task information is displayed, including \u003Cstrong\u003ETask Details\u003C/strong\u003E, \u003Cstrong\u003EGraph\u003C/strong\u003E, and \u003Cstrong\u003ERun History\u003C/strong\u003E sub-tabs.\u003C/li\u003E\u003Cli\u003ESelect the \u003Cstrong\u003EGraph\u003C/strong\u003E tab. The task graph appears, displaying a hierarchy of child tasks.\u003C/li\u003E\u003Cli\u003ESelect a task to view its details.\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EHere's what the task graph looks like:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_task_graph.png?v=df037233\" alt=\"assets/snowsight_task_graph.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EAnd here's an example of the task run history (shown after a few executions have taken place):\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_task_run_history.png?v=df037233\" alt=\"assets/snowsight_task_run_history.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFor more details, and to learn about viewing account level task history, please check out our \u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight-tasks.html\"\u003EViewing Task History\u003C/a\u003E documentation.\u003C/p\u003E\n","\u003Ch3\u003EExecuting the DAG\u003C/h3\u003E\n","\u003Cp\u003EThe easiest way to manually kick off the Task DAG execution is to open up the root \u003Ccode\u003EDEMO_DAG\u003C/code\u003E task, click on the "Graph" tab and then click on the "Run Task Graph" play button above the diagram. If not already set, you may have to pick a warehouse to use.\u003C/p\u003E\n","\u003Ch3\u003ETask Metadata\u003C/h3\u003E\n","\u003Cp\u003ESnowflake keeps metadata for almost everything you do, and makes that metadata available for you to query (and to create any type of process around). Tasks are no different, Snowflake maintains rich metadata to help you monitor your task runs. Here are a few sample SQL queries you can use to monitor your tasks runs:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E-- Get a list of tasks\nSHOW TASKS;\n\n-- Task execution history in the past day\nSELECT *\nFROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY(\n    SCHEDULED_TIME_RANGE_START=>DATEADD('DAY',-1,CURRENT_TIMESTAMP()),\n    RESULT_LIMIT => 100))\nORDER BY SCHEDULED_TIME DESC\n;\n\n-- Scheduled task runs\nSELECT\n    TIMESTAMPDIFF(SECOND, CURRENT_TIMESTAMP, SCHEDULED_TIME) NEXT_RUN,\n    SCHEDULED_TIME,\n    NAME,\n    STATE\nFROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY())\nWHERE STATE = 'SCHEDULED'\nORDER BY COMPLETED_TIME DESC;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EDeploy to Production\u003C/h2\u003E\n","\u003Cp\u003EDuring this step we will be deploying our Notebooks to production using a CI/CD pipeline. We will make a small change to a Notebook and then commit that change to our Git repo all within Snowsight. After that we will create a Pull Request (or PR), merge our changes to \u003Ccode\u003Emain\u003C/code\u003E and deploy with GitHub Actions. To put this in context, we are on step \u003Cstrong\u003E#7\u003C/strong\u003E in our data flow overview:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003ECreate a Snowflake Personal Access Token\u003C/h3\u003E\n","\u003Cp\u003EIn order to connect to your Snowflake account from GitHub Actions, we will use a Snowflake Personal Access Token (or PAT). Please follow the steps in \u003Ca href=\"https://docs.snowflake.com/en/user-guide/programmatic-access-tokens#generating-a-programmatic-access-token\"\u003EGenerating a programmatic access token\u003C/a\u003E to create a Snowflake PAT for your user. Use these values when creating the PAT, in the "New programmatic access token" dialog:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003EName\u003C/strong\u003E: DEMO_PAT\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EExpires in\u003C/strong\u003E: Leave with default (15 days)\u003C/li\u003E\u003Cli\u003E\u003Cstrong\u003EGrant access\u003C/strong\u003E: Select \u003Cstrong\u003ESingle role (recommended)\u003C/strong\u003E, then the \u003Ccode\u003EDEMO_ROLE\u003C/code\u003E role\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003EMake sure to save the PAT before leaving the page, as you won't be able to view it again.\u003C/p\u003E\n","\u003Cp\u003EFinally, run the following command in a SQL script in Workspaces. This will allow you to bypass the active network policy rule temporarily, for 60 minutes, in order to test out the CI/CD pipeline. For long-term access you need to create a network policy allowing access from the GitHub Actions environment. For more details check out our \u003Ca href=\"https://docs.snowflake.com/en/user-guide/network-policies\"\u003EControlling network traffic with network policies\u003C/a\u003E page.\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EALTER USER <your user name> MODIFY PROGRAMMATIC ACCESS TOKEN DEMO_PAT\n  SET MINS_TO_BYPASS_NETWORK_POLICY_REQUIREMENT = 60;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Ch3\u003EConfigure GitHub Actions\u003C/h3\u003E\n","\u003Cp\u003EBy default GitHub Actions disables any workflows (or CI/CD pipelines) defined in the forked repository. This repository contains a workflow to deploy your Snowpark Notebooks, which we'll use later on. So for now enable this workflow by opening your forked repository in GitHub, clicking on the \u003Ccode\u003EActions\u003C/code\u003E tab near the top middle of the page, and then clicking on the \u003Ccode\u003EI understand my workflows, go ahead and enable them\u003C/code\u003E green button.\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_activate.png?v=df037233\" alt=\"assets/github_actions_activate.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EThe last step to enable your GitHub Actions workflow is to create the required secrets. In order for your GitHub Actions workflow to be able to connect to your Snowflake account you will need to store your Snowflake credentials in GitHub. Action Secrets in GitHub are used to securely store values/variables which will be used in your CI/CD pipelines. In this step we will create secrets for each of the parameters used to connect to your Snowflake account.\u003C/p\u003E\n","\u003Cp\u003EFrom the repository, click on the "Settings" tab near the top of the page. From the Settings page, click on the \u003Ccode\u003ESecrets and variables\u003C/code\u003E then \u003Ccode\u003EActions\u003C/code\u003E tab in the left hand navigation. The \u003Ccode\u003EActions\u003C/code\u003E secrets should be selected. For each secret listed below click on \u003Ccode\u003ENew repository secret\u003C/code\u003E near the top right and enter the name given below along with the appropriate value (adjusting as appropriate).\u003C/p\u003E\n\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ESecret name\u003C/th\u003E\u003Cth colspan=\"1\" rowspan=\"1\"\u003ESecret value\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_ACCOUNT\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E<your account name>\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_USER\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E<your user name>\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_PASSWORD\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003E<your PAT>\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_ROLE\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EDEMO_ROLE\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_WAREHOUSE\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EDEMO_WH\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_DATABASE\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EDEMO_DB\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003ESNOWFLAKE_SCHEMA\u003C/td\u003E\u003Ctd colspan=\"1\" rowspan=\"1\"\u003EINTEGRATIONS\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETip\u003C/strong\u003E - For more details on how to structure the account name in SNOWFLAKE_ACCOUNT, see the account name discussion in \u003Ca href=\"https://docs.snowflake.com/en/user-guide/python-connector-install.html#step-2-verify-your-installation\"\u003Ethe Snowflake Python Connector install guide\u003C/a\u003E.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Cp\u003EWhen you’re finished adding all the secrets, the page should look like this:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_secrets.png?v=df037233\" alt=\"assets/github_actions_secrets.png\"\u003E\u003C/p\u003E\n\u003Cblockquote\u003E\n","\u003Cp\u003E\u003Cstrong\u003ETip\u003C/strong\u003E - For an even better solution to managing your secrets, you can leverage \u003Ca href=\"https://docs.github.com/en/actions/reference/environments\"\u003EGitHub Actions Environments\u003C/a\u003E. Environments allow you to group secrets together and define protection rules for each of your environments.\u003C/p\u003E\n\u003C/blockquote\u003E\n","\u003Ch3\u003EUpdate the 01 Notebook\u003C/h3\u003E\n","\u003Cp\u003ELet's make a change to the \u003Ccode\u003E01_load_excel_files\u003C/code\u003E Notebook and commit it to our forked repository. So begin by opening the \u003Ccode\u003E01_load_excel_files\u003C/code\u003E Notebook. For this Quickstart we will make a trivial change just so we can see how the overall process works. So scroll down to the bottom to the \u003Ccode\u003Esql_debugging\u003C/code\u003E cell and uncomment the final line, like this:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003E--DESCRIBE TABLE LOCATION;\n--SELECT * FROM LOCATION;\nSHOW TABLES;\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EIn the left sidebar you will now see the letter "M" next to the \u003Ccode\u003E01_load_excel_files.ipynb\u003C/code\u003E Notebook file indicating that you've modified it. To commit this change to the \u003Ccode\u003Edev\u003C/code\u003E branch, first switch to the \u003Cstrong\u003EChanges\u003C/strong\u003E tab, then click on the "Push" button near the top of the \u003Cstrong\u003EChanges\u003C/strong\u003E pane. Enter a basic commit message in the "Write commit message" dialog and click on the "Push" button at the bottom.\u003C/p\u003E\n","\u003Cp\u003EOnce that completes you will have committed your first change to your forked Git repository.\u003C/p\u003E\n","\u003Ch3\u003ECreate PR and Merge to Main\u003C/h3\u003E\n","\u003Cp\u003EIn order to create the Pull Request (PR) and merge our changes to the \u003Ccode\u003Emain\u003C/code\u003E branch we will need to use the GitHub UI. So toggle back over to your GitHub repository and open up the main repository code page by clicking on the "<> Code" tab near the top of the page. In order to create the PR you will need to switch to the \u003Ccode\u003Edev\u003C/code\u003E branch. To do this, simply click on the branch selector just above the list of files in the repository and click on the \u003Ccode\u003Edev\u003C/code\u003E branch.\u003C/p\u003E\n","\u003Cp\u003ENext click on the "Contribute" button just below the branch selector and click on the green "Open pull request" button (see screenshot below).\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_changes.png?v=df037233\" alt=\"assets/github_repo_changes.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003E\u003Cstrong\u003EImportant\u003C/strong\u003E: By default GitHub will compare the \u003Ccode\u003Edev\u003C/code\u003E branch in your forked repository with the \u003Ccode\u003Emain\u003C/code\u003E branch in the official Quickstart repository. You must change this. To change it click on the drop down that says "base repository" and change it to your forked repository. It should start with your GitHub username, not with "Snowflake-Labs" (see screenshot below).\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_pr_change_base.png?v=df037233\" alt=\"assets/github_repo_pr_change_base.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EOnce you change it the "Comparing changes" box should look like this:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_pr_change_base2.png?v=df037233\" alt=\"assets/github_repo_pr_change_base2.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EFinally enter a simple title and description, and then scroll down to verify that the change you made appears correctly. Then click on the green "Create pull request" button. You will be taken to the PR page.\u003C/p\u003E\n","\u003Cp\u003ETo merge the PR all you need to do is click on the green "Merge pull request" button and then click on the green "Confirm merge" button that appears. You will see a message saying "Pull request successfully merged and closed". At this point the changes have been merged to the \u003Ccode\u003Emain\u003C/code\u003E branch, the PR has been closed, and the GitHub Actions CI/CD pipeline has been initiated.\u003C/p\u003E\n","\u003Ch3\u003EGitHub Action Pipeline\u003C/h3\u003E\n","\u003Cp\u003EThis repository is already set up with a very simple GitHub Actions CI/CD pipeline. You can review the code for the workflow by opening the \u003Ccode\u003E.github/workflows/deploy_demo_objects.yaml\u003C/code\u003E file in the GitHub repo file explorer.\u003C/p\u003E\n","\u003Cp\u003EAs soon as you pushed the changes to your GitHub forked repo the workflow kicked off. To view the results go back to the homepage for your GitHub repository and do the following:\u003C/p\u003E\n\u003Cul\u003E\u003Cli\u003EFrom the repository, click on the \u003Ccode\u003EActions\u003C/code\u003E tab near the top middle of the page\u003C/li\u003E\u003Cli\u003EIn the left navigation bar click on the name of the workflow \u003Ccode\u003EDeploy Demo Objects\u003C/code\u003E\u003C/li\u003E\u003Cli\u003EClick on the name of most recent specific run (which should match the comment you entered)\u003C/li\u003E\u003Cli\u003EFrom the run overview page click on the \u003Ccode\u003Edeploy\u003C/code\u003E job and then browse through the output from the various steps. In particular you might want to review the output from the \u003Ccode\u003EDeploy Notebooks\u003C/code\u003E step.\u003C/li\u003E\u003C/ul\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_run_summary.png?v=df037233\" alt=\"assets/github_actions_run_summary.png\"\u003E\u003C/p\u003E\n","\u003Ch3\u003EGitHub Actions Workflow\u003C/h3\u003E\n","\u003Cp\u003ESo what exactly happened when the GitHub Actions CI/CD pipeline ran? Let's take a quick look at the \u003Ccode\u003E.github/workflows/deploy_demo_objects.yaml\u003C/code\u003E workflow definition to see. Here is the core part:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-yaml\"\u003Ejobs:\n  deploy:\n    runs-on: ubuntu-latest\n\n    steps:\n      - name: Checkout repository\n        uses: actions/checkout@v4\n\n      - name: Setup Python 3.10\n        uses: actions/setup-python@v5\n        with:\n          python-version: '3.10'\n\n      - name: Install Python packages\n        run: pip install -r requirements.txt\n\n      - name: Deploy notebooks\n        env:\n          SNOWFLAKE_ACCOUNT: ${{ secrets.SNOWFLAKE_ACCOUNT }}\n          SNOWFLAKE_USER: ${{ secrets.SNOWFLAKE_USER }}\n          SNOWFLAKE_PASSWORD: ${{ secrets.SNOWFLAKE_PASSWORD }}\n          SNOWFLAKE_ROLE: ${{ secrets.SNOWFLAKE_ROLE }}\n          SNOWFLAKE_WAREHOUSE: ${{ secrets.SNOWFLAKE_WAREHOUSE }}\n          SNOWFLAKE_DATABASE: ${{ secrets.SNOWFLAKE_DATABASE }}\n          SNOWFLAKE_SCHEMA: ${{ secrets.SNOWFLAKE_SCHEMA }}\n        run: |\n          python scripts/deploy_notebooks.py DEMO_DB PROD_SCHEMA NOTEBOOK_PIPELINES ./notebooks\n          python scripts/deploy_task_dag.py DEMO_DB PROD_SCHEMA NOTEBOOK_PIPELINES\n\u003C/code\u003E\u003C/pre\u003E\n","\u003Cp\u003EWe're running two Python scripts for the deployment:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003Edeploy_notebooks.py\u003C/strong\u003E: This script uploads the notebook files to a temporary stage and creates (or updates) the Notebook Project Object in the \u003Ccode\u003EPROD_SCHEMA\u003C/code\u003E. It uses the Snowpark Python API to interact with Snowflake.\u003C/p\u003E\n\u003C/li\u003E\u003Cli\u003E\n","\u003Cp\u003E\u003Cstrong\u003Edeploy_task_dag.py\u003C/strong\u003E: This script creates the Task DAG using the Python Task DAG API. Each task calls \u003Ccode\u003EEXECUTE NOTEBOOK PROJECT\u003C/code\u003E to run the appropriate notebook from our NPO.\u003C/p\u003E\n\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003ENotice that the scripts use environment variables for Snowflake credentials, which are populated from GitHub Secrets. This keeps your credentials secure and out of your code.\u003C/p\u003E\n","\u003Ch3\u003EExecuting the Production DAG\u003C/h3\u003E\n","\u003Cp\u003EThe GitHub Actions deployment pipeline just deployed the production version of both your Notebook Project object (which contains the actual notebook files) and your Task DAG, into the \u003Ccode\u003EPROD_SCHEMA\u003C/code\u003E. The final step here is optional, but if you want to actually run the production version of your Notebooks you'll need to manually execute the production version of the Task DAG as follows:\u003C/p\u003E\n\u003Col\u003E\u003Cli\u003EIn the Snowsight navigation menu, click \u003Cstrong\u003ECatalog\u003C/strong\u003E » \u003Cstrong\u003EDatabase Explorer\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003EIn the \u003Cstrong\u003EDatabase Explorer\u003C/strong\u003E pane, navigate to the \u003Ccode\u003EDEMO_DB\u003C/code\u003E database and \u003Ccode\u003EPROD_SCHEMA\u003C/code\u003E schema\u003C/li\u003E\u003Cli\u003EFor the selected schema, select and expand \u003Cstrong\u003ETasks\u003C/strong\u003E\u003C/li\u003E\u003Cli\u003ESelect the root \u003Ccode\u003EDEMO_DAG\u003C/code\u003E task\u003C/li\u003E\u003Cli\u003ESelect the \u003Cstrong\u003EGraph\u003C/strong\u003E tab\u003C/li\u003E\u003Cli\u003EClick on the "Run Task Graph" play button above the diagram (and if not already set, you may have to pick a warehouse to execute)\u003C/li\u003E\u003C/ol\u003E\n","\u003Cp\u003EAlternatively, you can run the DAG manually using SQL:\u003C/p\u003E\n\u003Cpre\u003E\u003Ccode class=\"language-sql\"\u003EUSE ROLE DEMO_ROLE;\nEXECUTE TASK DEMO_DB.PROD_SCHEMA.DEMO_DAG;\n\u003C/code\u003E\u003C/pre\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003ETeardown\u003C/h2\u003E\n","\u003Cp\u003EOnce you're finished with the Quickstart and want to clean things up, toggle back to the \u003Ccode\u003E00_start_here\u003C/code\u003E Notebook and scroll down to the "Step 08 Teardown" section. Then just run the SQL commands in the \u003Ccode\u003Esql_step08_teardown\u003C/code\u003E cell to remove all the objects created during the Quickstart.\u003C/p\u003E\n","\u003Cp\u003EFinally, if you want, you can also delete the demo Workspace you created and the forked copy of the repository in your GitHub account.\u003C/p\u003E\n<!-- ------------------------ -->\n","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E\n","\u003Cp\u003ECongratulations! You have now built end-to-end data engineering pipelines with Notebooks in Snowflake. You've also seen how to follow a complete Software Development Life Cycle (SDLC) for data engineering with Notebooks, including integration with Git, deploying to multiple environments through a CI/CD pipeline, instrumenting your code for monitoring and debugging, and orchestrating the pipelines with Task DAGs. Here's a quick visual recap:\u003C/p\u003E\n","\u003Cp\u003E\u003Cimg src=\"https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233\" alt=\"assets/quickstart_overview.png\"\u003E\u003C/p\u003E\n","\u003Cp\u003EHopefully you now have the building blocks, and examples, you need to get started building your own data engineering pipelines with Notebooks. So, what will you build now?\u003C/p\u003E\n","\u003Ch3\u003EWhat You Learned\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003EHow to ingest custom file formats (like Excel) with Snowpark from an external stage (such as an S3 bucket) into a Snowflake table\u003C/li\u003E\u003Cli\u003EHow to access data from Snowflake Marketplace and use it for your analysis\u003C/li\u003E\u003Cli\u003EHow to use Snowflake Notebooks and the Snowpark DataFrame API to build data engineering pipelines\u003C/li\u003E\u003Cli\u003EHow to add logging to your Python data engineering code and monitor from within Snowsight\u003C/li\u003E\u003Cli\u003EHow to use the Snowflake Python Management API to programmatically work with Snowflake objects\u003C/li\u003E\u003Cli\u003EHow to use the Python Task DAG API to programmatically manage Snowflake Tasks\u003C/li\u003E\u003Cli\u003EHow to use Cortex Code to accelerate data engineering development directly in Snowsight\u003C/li\u003E\u003Cli\u003EHow to build CI/CD pipelines using Snowflake's Git Integration, the Snowflake CLI, and GitHub Actions\u003C/li\u003E\u003Cli\u003EHow to deploy Snowflake Notebooks from dev to production\u003C/li\u003E\u003C/ul\u003E\n","\u003Ch3\u003ERelated Resources\u003C/h3\u003E\n\u003Cul\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/sfguide-data-engineering-with-notebooks\"\u003ESource Code on GitHub\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"/en/developers/guides/data-engineering-pipelines-with-snowpark-python/\"\u003EData Engineering Pipelines with Snowpark Python\u003C/a\u003E (Advanced Quickstart)\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-overview\"\u003ESnowflake Notebooks in Workspaces\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-schedule\"\u003ERun and Schedule Notebooks in Workspaces\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git\"\u003EGit-integrated Workspaces\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-cli/index\"\u003ESnowflake CLI\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview\"\u003ESnowflake Python Management API\u003C/a\u003E\u003C/li\u003E\u003Cli\u003E\u003Ca href=\"https://github.com/Snowflake-Labs/sfquickstarts/blob/master/site/sfguides/src/data-engineering-with-notebooks/assets/quickstart_overview.png\"\u003EDownload Reference Architecture\u003C/a\u003E\u003C/li\u003E\u003C/ul\u003E"],"title":"Getting Started with Data Engineering using Snowflake Notebooks",":items":{},":itemsOrder":[],"isDeveloperGuidesPage":false,":type":"snowflake-site/components/contentfragment","elements":{"quickstartArticleBody":{"dataType":"string","title":"Quickstart Article Body","value":"\u003C!-- ------------------------ --\u003E\n## Overview \n\nNotebooks are a very popular tool that are used to do everything from ad-hoc exploration of data to productionalized data engineering pipelines. While Notebooks can contain a mix of both Python and SQL, most of the time they're used for Python coding. In my previous Quickstart I detailed [how to build Python data engineering pipelines in Snowflake](/en/developers/guides/data-engineering-pipelines-with-snowpark-python/) using Visual Studio Code, from a lower-level developer perspective.\n\nThis Quickstart will focus on how to build Python data engineering pipelines using Snowflake native Notebooks! Additionally, it will provide all the details needed to manage and deploy those Notebooks through an automated CI/CD pipeline from development to production! Here's a quick visual overview of what we'll accomplish in this Quickstart:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### What You’ll Learn\n* How to ingest custom file formats (like Excel) with Snowpark from an external stage (such as an S3 bucket) into a Snowflake table\n* How to access data from Snowflake Marketplace and use it for your analysis\n* How to use Snowflake Notebooks and the Snowpark DataFrame API to build data engineering pipelines\n* How to add logging to your Python data engineering code and monitor from within Snowsight\n* How to use the Snowflake Python Management API to programmatically work with Snowflake objects\n* How to use the Python Task DAG API to programmatically manage Snowflake Tasks\n* How to use Cortex Code to accelerate data engineering development directly in Snowsight\n* How to build CI/CD pipelines using Snowflake's Git Integration, the Snowflake CLI, and GitHub Actions\n* How to deploy Snowflake Notebooks from dev to production\n\n### What You'll Build\n* A data share from the Snowflake Marketplace to access weather data\n* A data engineering pipeline with a Notebook to ingest Excel files into Snowflake\n* A data engineering pipeline with a Notebook to transform and aggregate data\n* A DAG (or Directed Acyclic Graph) of Tasks to orchestrate/schedule the pipelines\n* A CI/CD pipeline to deploy the Notebooks to production\n\n### Prerequisites\n* Familiarity with Python\n* Familiarity with the DataFrame API\n* Familiarity with Snowflake\n* Familiarity with Git repositories and GitHub\n\n### What You’ll Need\nYou will need the following things before beginning:\n\n* Snowflake account\n    * **A Snowflake Account**. Visit the [Snowflake Account Sign In](https://app.snowflake.com/) page to log into your account or to sign up for a trial account (we recommend Enterprise).\n    * **A Snowflake user created with ACCOUNTADMIN permissions**. This user will be used to get things setup in Snowflake.\n* GitHub account\n    * **A GitHub account**. If you don't already have a GitHub account you can create one for free. Visit the [Join GitHub](https://github.com/signup) page to get started.\n\n\n\u003C!-- ------------------------ --\u003E\n## Quickstart Setup\n\n### Create a GitHub Personal Access Token\nIn order for Snowflake to authenticate to your GitHub repository, you will need to generate a personal access token. Please follow the [Creating a personal access token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens#creating-a-personal-access-token-classic) instructions to create your token.\n\nMake sure to save the token before leaving the page, as we will be using it a couple of times during this Quickstart.\n\n### Fork the Quickstart Repository\nYou'll need to create a fork of the repository for this Quickstart in your GitHub account. Visit the [Data Engineering with Snowflake Notebooks associated GitHub Repository](https://github.com/Snowflake-Labs/sfguide-data-engineering-with-notebooks) and click on the \"Fork\" button near the top right. Complete any required fields and click \"Create Fork\".\n\n\n\u003C!-- ------------------------ --\u003E\n## Setup Snowflake\n\nIn this section we're going to set up the required objects in Snowflake to use notebooks in Workspaces and have that Workspace connected directly to our forked Git repository.\n\n### Create GitHub API Integration\n\nTo connect a Workspace to your GitHub repository, you'll need to create an API integration that allows Snowflake to communicate with GitHub. In your Snowflake environment, run the following in a SQL script in your default Workspace:\n\n```sql\nUSE ROLE ACCOUNTADMIN;\n\nCREATE OR REPLACE API INTEGRATION GITHUB_API_INTEGRATION\n    API_PROVIDER = GIT_HTTPS_API\n    API_ALLOWED_PREFIXES = ('https://github.com/')\n    ALLOWED_AUTHENTICATION_SECRETS = ALL\n    ENABLED = TRUE;\n```\n\nThis API integration allows Snowflake to access GitHub repositories. The `ALLOWED_AUTHENTICATION_SECRETS = ALL` setting allows the integration to use any secret for authentication, which we'll need for private repositories or to push changes back to GitHub.\n\n\u003E **Note**: Only users with ACCOUNTADMIN privileges (or the CREATE INTEGRATION privilege) can create API integrations. If you don't have these privileges, ask your Snowflake administrator to create this integration for you.\n\n\u003E **Note**: If you'd rather authenticate to GitHub using OAuth, instead of PAT, follow the steps in [Configure for authenticating with OAuth](https://docs.snowflake.com/en/developer-guide/git/git-setting-up-public#configure-for-authenticating-with-oauth) and use that `CREATE OR REPLACE API INTEGRATION` statement instead.\n\n### Create Workspace\n\nNow let's create a Git-integrated workspace connected to your forked repository. Workspaces provide a unified development environment where you can create, organize, and manage notebooks and other code files. Git-integrated workspaces allow you to sync your work with a Git repository for version control and collaboration.\n\n1. In the left navigation menu, select **Projects → Workspaces**\n\n2. In the Workspaces menu at the top left, under \"+\", select **Git workspace**\n\n3. In the \"Create Workspace\" dialog:\n   - **Repository URL**: Paste the URL of your forked repository (e.g., `https://github.com/YOUR_USERNAME/sfguide-data-engineering-with-notebooks`)\n   - **Workspace name**: Leave it as-is, or enter a name you prefer (e.g., `sfguide-data-engineering-with-notebooks`)\n   - **API Integration**: Select the `GITHUB_API_INTEGRATION` we created from the dropdown\n   - **Authentication method**: Select `Personal access token`\n   - **Credentials secret**: Select your \"USER$<username>\" database and the \"PUBLIC\" schema\n\n4. For authentication, select **Personal access token** and then click **+ Secret** to create a new secret with your GitHub Personal Access Token\n\n5. Click **Create**\n\nSnowflake will now clone the repository and create your workspace. This may take a few moments. Once complete, you'll see all the files from the GitHub repository in the left pane of your workspace. You can now open these files directly within Snowflake.\n\n\u003E **Note** - The Workspace provides a Jupyter-compatible notebook experience with direct access to governed Snowflake data. Notebooks run in a pre-built container environment optimized for AI/ML development with fully-managed access to CPUs and GPUs.\n\n\u003E **Note**: If you'd rather authenticate to GitHub using OAuth, instead of PAT, select `OAuth2` instead of `Personal access token` in \"Authentication method\" and follow the steps for OAuth2 authentication in [Create a Git workspace](https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git#create-a-git-workspace).\n\n\n### Create Demo Objects in Snowflake\n\nNext we will create the Snowflake objects used during this Guide. To do that we will run a SQL script from our new Workspace:\n\n1. In your Workspace, in the left \"Files\" pane, open the file `scripts/setup.sql`\n1. Run all of the SQL statements in this script by clicking on the blue down arrow and \"Run all\", next to play button at the top of the script, or using the shortcut CMD/CTRL+Shift+Enter\n\n### Create and Switch to Dev Branch\n\nDuring this Quickstart we will do our development work in a `dev` branch of the repository. One of the great features of Git-integrated Workspaces is the ability to create and manage branches directly within Snowsight.\n\nLet's create the `dev` branch now:\n\n1. In your Workspace, look at the top of the file explorer pane on the left\n2. Click on the **Changes** tab to open the Git panel\n3. You'll see the current branch displayed (likely `main`)\n4. Click on the branch dropdown to open the branch selector\n5. Click **+ New** to create a new branch\n6. Enter \"dev\" (all lowercase) as the branch name and click **Create**\n\nYour new `dev` branch will be created and you'll automatically be switched to it. You can verify this by looking at the branch name displayed in the Changes panel.\n\nOnce you're on the `dev` branch, you're ready to start running the setup cells.\n\n### Create the Notebook Service\n\nNotebooks in Workspaces run on Snowpark Container Services (SPCS) compute pools rather than traditional warehouses. A compute pool in Snowflake is a collection of virtual machine (VM) nodes that run containerized workloads. Snowflake provides a default system compute pool, which is available to all accounts, that we will use for this Quickstart, named `SYSTEM_COMPUTE_POOL_CPU`.\n\nBut before you can run notebooks interactively, you need to create a notebook service in the default system compute pool. A notebook service is a Snowflake-managed container service that hosts the notebook kernel and executes your code. Each notebook service is scoped to a single user and can be shared by multiple notebooks.\n\n\u003E **Note** - Notebook services can currently only be created through the Workspaces UI, not via SQL.\n\nTo create your notebook service:\n\n1. In your Workspace, open the `00_start_here.ipynb` Notebook\n2. Click the **Connect** button at the top of the notebook\n3. Enter the following values in the \"Connect your notebook\" dialog (and expand \"Service settings\"):\n   - **Service name**: Enter `NOTEBOOK_SERVICE`\n   - **Artifact repositories (optional)**: Select `SNOWFLAKE.SNOWPARK.PYPI_SHARED_REPOSITORY`\n   - **Service settings**:\n      - **Compute type**: Leave with default of `CPU`\n      - **Python version**: Leave with default\n      - **Runtime version**: Leave with default\n      - **Compute pool**: Select `SYSTEM_COMPUTE_POOL_CPU`\n      - **Idle timeout**: Select `1 hour`\n4. Click **Create and connect**\n\nThe notebook service will start up, which may take a minute or two for the first time. Once connected, you'll see a green \"Connected\" indicator.\n\nThe Snowflake Artifact Repository allows you to install third-party packages in your notebooks. And in this case we're using Snowflake’s default PyPI Artifact Repository to install PyPI packages. Check out [Using artifact repositories](https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-artifact-repositories) for more details.\n\n\u003E **Tip** - Since notebook services can be shared across multiple notebooks, you only need to create one service. When you open other notebooks in your workspace, you can connect them to the same `NOTEBOOK_SERVICE` to share compute resources.\n\n\n\u003C!-- ------------------------ --\u003E\n## Load Weather\n\nDuring this step we will be \"loading\" the raw weather data to Snowflake. But \"loading\" is really the wrong word here. Because we're using Snowflake's unique data sharing capability we don't actually need to copy the data to our Snowflake account with a custom ETL process. Instead we can directly access the weather data shared by Pelmorex Weather Source in the Snowflake Marketplace. To put this in context, we are on step **#2** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### Load Weather Data from Snowflake Marketplace\nPelmorex Weather Source is a leading provider of global weather and climate data and their OnPoint Product Suite provides businesses with the necessary weather and climate data to quickly generate meaningful and actionable insights for a wide range of use cases across industries. Let's connect to the `Pelmorex Weather Source: Frostbyte` feed in the Snowflake Marketplace by following these steps:\n\n* Login to Snowsight\n* Click on the `Marketplace` -\u003E `Snowflake Marketplace` link in the left navigation bar\n* Enter \"Pelmorex Weather Source: Frostbyte\" in the search box and click return\n* Click on the \"Pelmorex Weather Source: Frostbyte\" listing tile\n* Click the blue \"Get\" button\n    * Expand the \"Options\" dialog\n    * Change the \"Database name\" to read \"FROSTBYTE_WEATHERSOURCE\" (all capital letters)\n    * Select the \"DEMO_ROLE\" role to have access to the new database\n* Click on the blue \"Get\" button\n\nThat's it... we don't have to do anything from here to keep this data updated. The provider will do that for us and data sharing means we are always seeing whatever they have published. How amazing is that? Just think of all the things you didn't have do here to get access to an always up-to-date, third-party dataset!\n\n\n\u003C!-- ------------------------ --\u003E\n## Load Excel Files\n\nDuring this step we will be loading data from two Excel files in S3 into the `LOCATION` and `ORDER_DETAIL` tables. To do this we'll take advantage of the [Snowpark Python file access feature](https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-sprocs#reading-dynamically-specified-files-with-snowflakefile). For more details on this please see my related blog post [Simplify data ingestion with Snowpark Python file access](https://medium.com/snowflake/simplify-data-ingestion-with-snowpark-python-file-access-f2bc0e4cd887).\n\n\u003E **Note** - Workspace Notebooks do not yet support [Scoped URLs](https://docs.snowflake.com/en/sql-reference/functions/build_scoped_file_url) or [Stage URLs](https://docs.snowflake.com/en/sql-reference/functions/build_stage_file_url). So as a workaround for now we will copy the Excel files from the external stage to a temporary internal stage and open from there. This note was last updated on 2/11/26.\n\nTo put this in context, we are on step **#3** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### Run the Notebook\n\nIn Workspaces, open the `01_load_excel_files` notebook,  click on the \"Run all\" button near the top right of the window. This will execute all cells in the notebook, in order.\n\n### Notebook Git Integration\n\nYou will notice that to the left of the main Notebook area there is a sidebar which shows the files in the Workspace. The two notebooks that we'll be running and deploying in this Quickstart can be found in the `/notebooks` folder. Above the file viewer you will see a **Changes** button/tab which contains the Git related controls that are built into Workspaces. Here you are able to work with branches, push and pull changes, and view diffs. Here's a screenshot:\n\n![assets/snowsight_notebook_git.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_notebook_git.png?v=df037233)\n\n### Notebook Cell References\n\nWorkspace Notebooks provide powerful interoperability between SQL and Python cells. You can easily pass data between cells using standard Jupyter patterns.\n\nFor example, you can run a SQL query in one cell and then use the results in a Python cell. The results of SQL cells are automatically available as DataFrames. Here's an example:\n\nIn the `sql_get_spreadsheets` SQL cell we have:\n```sql\nSELECT '@INTEGRATIONS.FROSTBYTE_RAW_STAGE/intro/order_detail.xlsx' AS STAGE_FILE_PATH, 'order_detail' AS WORKSHEET_NAME, 'ORDER_DETAIL' AS TARGET_TABLE\nUNION\nSELECT '@INTEGRATIONS.FROSTBYTE_RAW_STAGE/intro/location.xlsx', 'location', 'LOCATION';\n```\n\nAnd then in the subsequent `py_process_spreadsheets` Python cell we can access the prior result like this:\n```python\n# Process each file from the sql_get_spreadsheets cell above\nfiles_to_load = dataframe_1\nfor index, excel_file in files_to_load.iterrows():\n    print(f\"Processing Excel file {excel_file['STAGE_FILE_PATH']}\")\n    load_excel_worksheet_to_table(session, excel_file['STAGE_FILE_PATH'], excel_file['WORKSHEET_NAME'], excel_file['TARGET_TABLE'])\n```\n\nFor more details, please see the [Notebooks in Workspaces documentation](https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-edit-run) for information on cell references.\n\n### Dynamic File Access\n\nLike I mentioned at the beginning of this section, we're able to read and process Excel files with the [Snowpark Python file access feature](https://docs.snowflake.com/en/developer-guide/snowpark/python/creating-sprocs#reading-dynamically-specified-files-with-snowflakefile). And this same principle applies to more than just Excel files, you can use it to process any file format you'd like. For more details on this please see my related blog post [Simplify data ingestion with Snowpark Python file access](https://medium.com/snowflake/simplify-data-ingestion-with-snowpark-python-file-access-f2bc0e4cd887).\n\n\u003E **Note** - Workspace Notebooks do not yet support [Scoped URLs](https://docs.snowflake.com/en/sql-reference/functions/build_scoped_file_url) or [Stage URLs](https://docs.snowflake.com/en/sql-reference/functions/build_stage_file_url). So as a workaround for now we will copy the Excel files from the external stage to a temporary internal stage and open from there. This note was last updated on 2/11/26.\n\n\n\u003C!-- ------------------------ --\u003E\n## Load Daily City Metrics\n\nDuring this step we will be joining data from our `LOCATION` and `ORDER_DETAIL` tables (from the previous step) with the weather data we set up in step 2 to produce an aggregated reporting table `DAILY_CITY_METRICS`. We'll leverage the Snowpark DataFrame API to perform the data transformations, and will also show how to incorporate logging into your code. To put this in context, we are on step **#4** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### Run the Notebook\n\nOpen the `02_load_daily_city_metrics` Notebook click on the \"Run all\" button near the top right of the window. This will execute all cells in the notebook, in order.\n\n### Snowpark DataFrame API\n\nIn this step we're starting to really use the Snowpark DataFrame API for data transformations. The Snowpark API provides the same functionality as the [Spark SQL API](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/index.html). To begin with you need to create a Snowpark session object. Like in PySpark, this can be accomplished with the `Session.builder.configs().create()` methods. But within a Snowflake Notebook this is simplified and can be accomplished with just `session = get_active_session()`.\n\nOnce you have a Snowpark session you can begin working with data. In this Notebook we're using DataFrames to join the data from different tables into an `order_detail` DataFrame using the `join()` API.\n\n```python\norder_detail = order_detail.join(location, order_detail['LOCATION_ID'] == location['LOCATION_ID'])\norder_detail = order_detail.join(history_day, (F.builtin(\"DATE\")(order_detail['ORDER_TS']) == history_day['DATE_VALID_STD']) & (location['ISO_COUNTRY_CODE'] == history_day['COUNTRY']) & (location['CITY'] == history_day['CITY_NAME']))\n```\n\nAfter that we're then aggregating the DataFrame using APIs such as `agg()`, `group_by()`, and `select()`.\n\n```python\nfinal_agg = order_detail.group_by(F.col('DATE_VALID_STD'), F.col('CITY_NAME'), F.col('ISO_COUNTRY_CODE')) \\\n                        .agg( \\\n                            F.sum('PRICE').alias('DAILY_SALES_SUM'), \\\n                            F.avg('AVG_TEMPERATURE_AIR_2M_F').alias(\"AVG_TEMPERATURE_F\"), \\\n                            F.avg(\"TOT_PRECIPITATION_IN\").alias(\"AVG_PRECIPITATION_IN\"), \\\n                        ) \\\n                        .select(F.col(\"DATE_VALID_STD\").alias(\"DATE\"), F.col(\"CITY_NAME\"), F.col(\"ISO_COUNTRY_CODE\").alias(\"COUNTRY_DESC\"), \\\n                            F.builtin(\"ZEROIFNULL\")(F.col(\"DAILY_SALES_SUM\")).alias(\"DAILY_SALES\"), \\\n                            F.round(F.col(\"AVG_TEMPERATURE_F\"), 2).alias(\"AVG_TEMPERATURE_FAHRENHEIT\"), \\\n                            F.round(F.col(\"AVG_PRECIPITATION_IN\"), 2).alias(\"AVG_PRECIPITATION_INCHES\"), \\\n                        )\n```\n\nAnd finally if the target table exists we're using the `merge()` DataFrame API to perform an Upsert operation on the target table. This is what enables us to perform incremental processing.\n\n```python\n    dcm.merge(final_agg, (dcm['DATE'] == final_agg['DATE']) & (dcm['CITY_NAME'] == final_agg['CITY_NAME']) & (dcm['COUNTRY_DESC'] == final_agg['COUNTRY_DESC']), \\\n                        [F.when_matched().update(cols_to_update), F.when_not_matched().insert(cols_to_update)])\n```\n\nFor more details about the Snowpark Python DataFrame API, please check out our [Working with Dataframe in Snowpark Python](https://docs.snowflake.com/en/developer-guide/snowpark/python/working-with-dataframes.html) page.\n\n### Python Management API\n\nThe new Python Management API allows us to programmatically interact with Snowflake with native Python objects. This API can be used to both inspect and manage Snowflake objects. In the previous Quickstart we checked for the existence of an object by using SQL like this:\n\n```sql\ndef table_exists(session, database_name='', schema_name='', table_name=''):\n    exists = session.sql(\"SELECT EXISTS (SELECT * FROM {}.INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA = '{}' AND TABLE_NAME = '{}') AS TABLE_EXISTS\".format(database_name, schema_name, table_name)).collect()[0]['TABLE_EXISTS']\n    return exists\n```\n\nBut with the Python Management API this can now be done with native Python objects like this:\n\n```python\ndef table_exists(session, database_name='', schema_name='', table_name=''):\n    root = Root(session)\n    tables = root.databases[database_name].schemas[schema_name].tables.iter(like=table_name)\n    for table_obj in tables:\n        if table_obj.name == table_name:\n            return True\n\n    return False\n```\n\nAnd this is really just the beginning of what you can do with this new library. Please check out the [Snowflake Python Management API](https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview) documentation for more details.\n\n### Logging in Python\n\nA key aspect of building robust data engineering pipelines involves instrumenting our code. This enables the monitoring and operations of our code, and is especially important when automating the deployment and monitoring of our pipelines with DevOps. Snowflake has a rich set of [Logging and Tracing](https://docs.snowflake.com/en/developer-guide/logging-tracing/logging-tracing-overview) capabilities to help.\n\nYou'll notice that in the `py_initialize` cell of this Notebook we're using Snowflake's logging capabilities. There are two steps to do so in your code. The first is to create a logger to use:\n\n```python\nlogger_name = 'demo_logger'\nlogger = logging.getLogger(logger_name)\nlogger.setLevel(logging.INFO)\n```\n\nAnd the second is to actually log debugging and informational messages at the appropriate places in your code:\n\n```python\nlogger.info(f\"Begin executing notebook {notebook_name}\", extra = {'logger_name': logger_name})\n```\n\nIn addition to custom logging, Snowflake is instrumenting all services/features to take advantage of logging and tracing as well. For example, when you ran this Notebook earlier it logged a number of messages by default, like when each cell executed.\n\nAll of your log messages can be found in your default logging table, which we created in step 1. If you look back at the code from step 1 you'll find that we created an event table named `DEMO_DB.INTEGRATIONS.DEMO_EVENTS` and then set that as the default event table for the account. You can now use this table just like any other table in Snowflake to query and act on the log data.\n\nLet's view the logs that have been created so far by running the query in Step 04 of the `00_start_here` Notebook. Here's the query to do that:\n\n```python\nSELECT \n    TIMESTAMP,\n    VALUE AS LOG_MESSAGE,\n    RESOURCE_ATTRIBUTES:\"snow.service.name\"::string AS SERVICE_NAME,\n    RECORD_ATTRIBUTES:\"severity_text\"::string AS SEVERITY\nFROM DEMO_DB.INTEGRATIONS.DEMO_EVENTS\nWHERE RECORD_TYPE = 'LOG'\n--  AND RESOURCE_ATTRIBUTES:\"snow.service.name\" = 'NOTEBOOK_SERVICE'\n  AND TIMESTAMP \u003E DATEADD(hour, -1, CURRENT_TIMESTAMP())\nORDER BY TIMESTAMP DESC\nLIMIT 100;\n```\n\n\n\u003C!-- ------------------------ --\u003E\n## Using Cortex Code\n\nNow that we've built our data engineering pipelines, let's look at a tool that can help accelerate your development workflow significantly. [Cortex Code](https://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight) is an AI-powered coding assistant built directly into Snowsight that understands your Snowflake environment, including SQL worksheets, dbt Projects, and Notebooks. It can generate and modify code, explain existing logic, and even run notebooks — all from a conversational interface without ever leaving Snowsight.\n\nFor data engineers, this is a game changer. Instead of manually writing your Python DataFrame (or SQL) queries, you can describe what you want in plain English and Cortex Code will generate context-aware code that follows Snowflake best practices. Whether you're building a new transformation, adding a debugging query, or exploring unfamiliar data, Cortex Code helps you move faster while staying in your flow.\n\n\u003E **Note** - Cortex Code requires the `SNOWFLAKE.COPILOT_USER` database role and either the `SNOWFLAKE.CORTEX_USER` or `SNOWFLAKE.CORTEX_AGENT_USER` database role. It also requires [Cross-region inference](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cross-region-inference) to be enabled. See the [Cortex Code documentation](https://docs.snowflake.com/en/user-guide/cortex-code/cortex-code-snowsight) for full details.\n\n### Cortex Code in Action\n\nLet's see Cortex Code in action with the Notebook we just ran. Open the `02_load_daily_city_metrics` Notebook in your Workspace and then follow these steps:\n\n1. Click the Cortex Code icon in the lower-right corner of the Workspace to open the assistant panel\n2. In the message box, enter the following prompt and press Enter:\n\n```\nAdd a Python cell under the debugging section that uses Snowpark DataFrame to query the DAILY_CITY_METRICS table and show the top 10 cities by total sales, including total days and average temperature.\n```\n\nCortex Code will analyze the context of your Notebook and generate a new Python cell with the appropriate Snowpark DataFrame code. You'll be able to review the suggested change before applying it. Once you're happy with it, apply the change and run the new cell to see the results.\n\n![assets/cortex_code_snowsight.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/cortex_code_snowsight.png?v=df037233)\n\nWhile this was just a simple debugging cell, we can leverage Cortex Code to write any part (or all) of our pipelines for us! As you continue building out your data engineering pipelines, Cortex Code can help you iterate faster — from prototyping new transformations to troubleshooting issues in production.\n\n\n\u003C!-- ------------------------ --\u003E\n## Deploy Notebook Project to Dev\n\nDuring this step we will be deploying the dev versions of our two data engineering Notebooks: `01_load_excel_files` and `02_load_daily_city_metrics`. To deploy notebooks to Snowflake we will create a `NOTEBOOK PROJECT` object in our `DEV_SCHEMA`, along with the other resources in our development environment.\n\nTo put this in context, we are on step **#5** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### NOTEBOOK PROJECT Object\n\nNotebook Project Objects (NPOs) are the key to deploying and scheduling notebooks in production with Workspace Notebooks. An NPO is a schema-level object that encapsulates your notebook files and their dependencies, making them ready for scheduled execution.\n\nKey characteristics of NPOs:\n\n* **Schema-level object**: NPOs exist within a specific schema (`database_name.schema_name.npo_name`)\n* **Encapsulation**: An NPO captures all notebook files from your workspace, ensuring all dependencies are available during execution\n* **Versioning**: NPOs support versioned deployments, allowing you to track changes and roll back if needed\n* **Execution**: You execute an NPO using the `EXECUTE NOTEBOOK PROJECT` command, specifying which notebook file to run with the `MAIN_FILE` parameter\n\nThe NPO deployment model provides a clean separation between interactive development (in Workspaces) and production execution (via NPOs and Tasks). This ensures that your scheduled notebooks run exactly the code that was deployed, not whatever is currently in your workspace.\n\n### Deploy Notebooks\n\nTo deploy the dev versions of our notebooks, we'll create an NPO using a simple Python script. The `scripts/deploy_notebooks.py` script handles the deployment by:\n\n1. Getting a temporary stage from the Snowpark session\n2. Uploading all notebook files from the local folder to the stage\n3. Creating or updating the Notebook Project Object from the staged files\n\nRun the deployment cell in the `00_start_here` Notebook to deploy the notebooks. The cell uses the `%run` magic to execute the deployment script:\n\n```python\n%run scripts/deploy_notebooks.py DEMO_DB DEV_SCHEMA DEMO_PIPELINES_NP ./notebooks\n```\n\nThis command deploys all notebooks from the `./notebooks` folder to a Notebook Project Object named `DEMO_PIPELINES_NP` in `DEMO_DB.DEV_SCHEMA`.\n\nYou can verify the deployment by running:\n\n```sql\nSHOW NOTEBOOK PROJECTS IN DEMO_DB.DEV_SCHEMA;\n```\n\nOnce deployed, you'll be able to execute these notebooks on a schedule using Snowflake Tasks.\n\n\n\u003C!-- ------------------------ --\u003E\n## Orchestrate Pipelines\n\nDuring this step we will be orchestrating our new Snowpark Notebook pipelines with Snowflake's native orchestration feature named Tasks. You can create and deploy Snowflake Task objects using SQL as well as with our Python Task APIs. For this Quickstart, we will use Snowflake Python Task APIs to create the Tasks. We will create two tasks, one for each Notebook, and chain them together. To put this in context, we are on step **#6** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### Deploy Task DAG\n\nToggle back to the `00_start_here` Notebook, scroll down to the \"Step 06 Orchestrate Pipelines\" section, and run each of the cells.\n\n### Python Task DAG API\n\nIn this step we will create a DAG (or Directed Acyclic Graph) of Tasks using the new [Snowflake Python Management API](https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview). The Task DAG API builds upon the Python Management API to provide advanced Task management capabilities. And if you've used Airflow before, this Python API should look familiar as it's similar to the Airflow v1 Python API. For more details see [Managing Snowflake tasks and task graphs with Python](https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-managing-tasks).\n\nHere is the key part of the code:\n\n```python\n# Define the DAG\nwith DAG(dag_name, schedule=timedelta(days=1), warehouse=warehouse_name) as dag:\n    dag_task1 = DAGTask(\"LOAD_EXCEL_FILES_TASK\", definition=f'''\n        EXECUTE NOTEBOOK PROJECT {database_name}.{schema_name}.{notebook_project_name}\n            MAIN_FILE = '01_load_excel_files.ipynb'\n            COMPUTE_POOL = {compute_pool}\n            RUNTIME = '{runtime}'\n            QUERY_WAREHOUSE = {warehouse_name}\n            ARTIFACT_REPOSITORIES = ({artifact_repository})\n            ARGUMENTS = '--database-name {database_name} --schema-name {schema_name}'\n        ''', warehouse=warehouse_name)\n    dag_task2 = DAGTask(\"LOAD_DAILY_CITY_METRICS\", definition=f'''\n        EXECUTE NOTEBOOK PROJECT {database_name}.{schema_name}.{notebook_project_name}\n            MAIN_FILE = '02_load_daily_city_metrics.ipynb'\n            COMPUTE_POOL = {compute_pool}\n            RUNTIME = '{runtime}'\n            QUERY_WAREHOUSE = {warehouse_name}\n            ARGUMENTS = '--database-name {database_name} --schema-name {schema_name}'\n        ''', warehouse=warehouse_name)\n\n    # Define the dependencies between the tasks\n    dag_task1 \u003E\u003E dag_task2 # dag_task1 is a predecessor of dag_task2\n\n# Create the DAG in Snowflake\ndag_op.deploy(dag, mode=\"orreplace\")\n```\n\nYou can see that we're defining two tasks, one for each Notebook, and that each task calls `EXECUTE NOTEBOOK PROJECT` for the corresponding Notebook in our NPO. The key parameters are:\n\n* **MAIN_FILE**: The notebook file to execute within the NPO\n* **COMPUTE_POOL**: The SPCS compute pool to run the notebook on\n* **RUNTIME**: The container runtime version (e.g., `V2.5-CPU-PY3.12`)\n* **QUERY_WAREHOUSE**: The warehouse to use for SQL queries\n\nWe then define the dependencies and deploy the DAG. As you can see this makes managing complex Task DAGs much easier!\n\nThis code is also available in the `scripts/deploy_task_dag.py` script which could be used to automate the Task DAG deployment further.\n\n### Task Viewer in Snowsight\n\nNow, after your DAG is deployed, all the tasks in your DAG will be running as per the defined schedule. However, as a Snowflake user, how can you peek into the success and failure of each run, look at the task run time, and more?\n\nSnowflake provides some rich task observability features in the Snowsight UI. Try it out for yourself by following these steps:\n\n1. In the Snowsight left navigation menu, click **Catalog** » **Database Explorer**.\n1. In the \"Database Explorer\" pane, navigate to the `DEMO_DB` database and `DEV_SCHEMA` schema.\n1. For the selected schema, select and expand **Tasks**.\n1. Select the `DEMO_DAG` task. Task information is displayed, including **Task Details**, **Graph**, and **Run History** sub-tabs.\n1. Select the **Graph** tab. The task graph appears, displaying a hierarchy of child tasks.\n1. Select a task to view its details.\n\nHere's what the task graph looks like:\n\n![assets/snowsight_task_graph.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_task_graph.png?v=df037233)\n\nAnd here's an example of the task run history (shown after a few executions have taken place):\n\n![assets/snowsight_task_run_history.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/snowsight_task_run_history.png?v=df037233)\n\nFor more details, and to learn about viewing account level task history, please check out our [Viewing Task History](https://docs.snowflake.com/en/user-guide/ui-snowsight-tasks.html) documentation.\n\n### Executing the DAG\n\nThe easiest way to manually kick off the Task DAG execution is to open up the root `DEMO_DAG` task, click on the \"Graph\" tab and then click on the \"Run Task Graph\" play button above the diagram. If not already set, you may have to pick a warehouse to use.\n\n### Task Metadata\n\nSnowflake keeps metadata for almost everything you do, and makes that metadata available for you to query (and to create any type of process around). Tasks are no different, Snowflake maintains rich metadata to help you monitor your task runs. Here are a few sample SQL queries you can use to monitor your tasks runs:\n\n```sql\n-- Get a list of tasks\nSHOW TASKS;\n\n-- Task execution history in the past day\nSELECT *\nFROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY(\n    SCHEDULED_TIME_RANGE_START=\u003EDATEADD('DAY',-1,CURRENT_TIMESTAMP()),\n    RESULT_LIMIT =\u003E 100))\nORDER BY SCHEDULED_TIME DESC\n;\n\n-- Scheduled task runs\nSELECT\n    TIMESTAMPDIFF(SECOND, CURRENT_TIMESTAMP, SCHEDULED_TIME) NEXT_RUN,\n    SCHEDULED_TIME,\n    NAME,\n    STATE\nFROM TABLE(INFORMATION_SCHEMA.TASK_HISTORY())\nWHERE STATE = 'SCHEDULED'\nORDER BY COMPLETED_TIME DESC;\n```\n\n\u003C!-- ------------------------ --\u003E\n## Deploy to Production\n\nDuring this step we will be deploying our Notebooks to production using a CI/CD pipeline. We will make a small change to a Notebook and then commit that change to our Git repo all within Snowsight. After that we will create a Pull Request (or PR), merge our changes to `main` and deploy with GitHub Actions. To put this in context, we are on step **#7** in our data flow overview:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\n### Create a Snowflake Personal Access Token\nIn order to connect to your Snowflake account from GitHub Actions, we will use a Snowflake Personal Access Token (or PAT). Please follow the steps in [Generating a programmatic access token](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens#generating-a-programmatic-access-token) to create a Snowflake PAT for your user. Use these values when creating the PAT, in the \"New programmatic access token\" dialog:\n\n* **Name**: DEMO_PAT\n* **Expires in**: Leave with default (15 days)\n* **Grant access**: Select **Single role (recommended)**, then the `DEMO_ROLE` role\n\nMake sure to save the PAT before leaving the page, as you won't be able to view it again.\n\nFinally, run the following command in a SQL script in Workspaces. This will allow you to bypass the active network policy rule temporarily, for 60 minutes, in order to test out the CI/CD pipeline. For long-term access you need to create a network policy allowing access from the GitHub Actions environment. For more details check out our [Controlling network traffic with network policies](https://docs.snowflake.com/en/user-guide/network-policies) page.\n\n```sql\nALTER USER <your user name> MODIFY PROGRAMMATIC ACCESS TOKEN DEMO_PAT\n  SET MINS_TO_BYPASS_NETWORK_POLICY_REQUIREMENT = 60;\n```\n\n### Configure GitHub Actions\nBy default GitHub Actions disables any workflows (or CI/CD pipelines) defined in the forked repository. This repository contains a workflow to deploy your Snowpark Notebooks, which we'll use later on. So for now enable this workflow by opening your forked repository in GitHub, clicking on the `Actions` tab near the top middle of the page, and then clicking on the `I understand my workflows, go ahead and enable them` green button.\n\n![assets/github_actions_activate.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_activate.png?v=df037233)\n\nThe last step to enable your GitHub Actions workflow is to create the required secrets. In order for your GitHub Actions workflow to be able to connect to your Snowflake account you will need to store your Snowflake credentials in GitHub. Action Secrets in GitHub are used to securely store values/variables which will be used in your CI/CD pipelines. In this step we will create secrets for each of the parameters used to connect to your Snowflake account.\n\nFrom the repository, click on the \"Settings\" tab near the top of the page. From the Settings page, click on the `Secrets and variables` then `Actions` tab in the left hand navigation. The `Actions` secrets should be selected. For each secret listed below click on `New repository secret` near the top right and enter the name given below along with the appropriate value (adjusting as appropriate).\n\n| Secret name | Secret value |\n|-------------|--------------|\n| SNOWFLAKE_ACCOUNT | <your account name> |\n| SNOWFLAKE_USER | <your user name> |\n| SNOWFLAKE_PASSWORD | <your PAT> |\n| SNOWFLAKE_ROLE | DEMO_ROLE |\n| SNOWFLAKE_WAREHOUSE | DEMO_WH |\n| SNOWFLAKE_DATABASE | DEMO_DB |\n| SNOWFLAKE_SCHEMA | INTEGRATIONS |\n\n\u003E  **Tip** - For more details on how to structure the account name in SNOWFLAKE_ACCOUNT, see the account name discussion in [the Snowflake Python Connector install guide](https://docs.snowflake.com/en/user-guide/python-connector-install.html#step-2-verify-your-installation).\n\nWhen you’re finished adding all the secrets, the page should look like this:\n\n![assets/github_actions_secrets.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_secrets.png?v=df037233)\n\n\u003E  **Tip** - For an even better solution to managing your secrets, you can leverage [GitHub Actions Environments](https://docs.github.com/en/actions/reference/environments). Environments allow you to group secrets together and define protection rules for each of your environments.\n\n### Update the 01 Notebook\n\nLet's make a change to the `01_load_excel_files` Notebook and commit it to our forked repository. So begin by opening the `01_load_excel_files` Notebook. For this Quickstart we will make a trivial change just so we can see how the overall process works. So scroll down to the bottom to the `sql_debugging` cell and uncomment the final line, like this:\n\n```sql\n--DESCRIBE TABLE LOCATION;\n--SELECT * FROM LOCATION;\nSHOW TABLES;\n```\n\nIn the left sidebar you will now see the letter \"M\" next to the `01_load_excel_files.ipynb` Notebook file indicating that you've modified it. To commit this change to the `dev` branch, first switch to the **Changes** tab, then click on the \"Push\" button near the top of the **Changes** pane. Enter a basic commit message in the \"Write commit message\" dialog and click on the \"Push\" button at the bottom.\n\nOnce that completes you will have committed your first change to your forked Git repository.\n\n### Create PR and Merge to Main\n\nIn order to create the Pull Request (PR) and merge our changes to the `main` branch we will need to use the GitHub UI. So toggle back over to your GitHub repository and open up the main repository code page by clicking on the \"\u003C\u003E Code\" tab near the top of the page. In order to create the PR you will need to switch to the `dev` branch. To do this, simply click on the branch selector just above the list of files in the repository and click on the `dev` branch.\n\nNext click on the \"Contribute\" button just below the branch selector and click on the green \"Open pull request\" button (see screenshot below).\n\n![assets/github_repo_changes.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_changes.png?v=df037233)\n\n**Important**: By default GitHub will compare the `dev` branch in your forked repository with the `main` branch in the official Quickstart repository. You must change this. To change it click on the drop down that says \"base repository\" and change it to your forked repository. It should start with your GitHub username, not with \"Snowflake-Labs\" (see screenshot below).\n\n![assets/github_repo_pr_change_base.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_pr_change_base.png?v=df037233)\n\nOnce you change it the \"Comparing changes\" box should look like this:\n\n![assets/github_repo_pr_change_base2.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_repo_pr_change_base2.png?v=df037233)\n\nFinally enter a simple title and description, and then scroll down to verify that the change you made appears correctly. Then click on the green \"Create pull request\" button. You will be taken to the PR page.\n\nTo merge the PR all you need to do is click on the green \"Merge pull request\" button and then click on the green \"Confirm merge\" button that appears. You will see a message saying \"Pull request successfully merged and closed\". At this point the changes have been merged to the `main` branch, the PR has been closed, and the GitHub Actions CI/CD pipeline has been initiated.\n\n### GitHub Action Pipeline\n\nThis repository is already set up with a very simple GitHub Actions CI/CD pipeline. You can review the code for the workflow by opening the `.github/workflows/deploy_demo_objects.yaml` file in the GitHub repo file explorer.\n\nAs soon as you pushed the changes to your GitHub forked repo the workflow kicked off. To view the results go back to the homepage for your GitHub repository and do the following:\n\n* From the repository, click on the `Actions` tab near the top middle of the page\n* In the left navigation bar click on the name of the workflow `Deploy Demo Objects`\n* Click on the name of most recent specific run (which should match the comment you entered)\n* From the run overview page click on the `deploy` job and then browse through the output from the various steps. In particular you might want to review the output from the `Deploy Notebooks` step.\n\n![assets/github_actions_run_summary.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/github_actions_run_summary.png?v=df037233)\n\n### GitHub Actions Workflow\n\nSo what exactly happened when the GitHub Actions CI/CD pipeline ran? Let's take a quick look at the `.github/workflows/deploy_demo_objects.yaml` workflow definition to see. Here is the core part:\n\n```yaml\njobs:\n  deploy:\n    runs-on: ubuntu-latest\n\n    steps:\n      - name: Checkout repository\n        uses: actions/checkout@v4\n\n      - name: Setup Python 3.10\n        uses: actions/setup-python@v5\n        with:\n          python-version: '3.10'\n\n      - name: Install Python packages\n        run: pip install -r requirements.txt\n\n      - name: Deploy notebooks\n        env:\n          SNOWFLAKE_ACCOUNT: ${{ secrets.SNOWFLAKE_ACCOUNT }}\n          SNOWFLAKE_USER: ${{ secrets.SNOWFLAKE_USER }}\n          SNOWFLAKE_PASSWORD: ${{ secrets.SNOWFLAKE_PASSWORD }}\n          SNOWFLAKE_ROLE: ${{ secrets.SNOWFLAKE_ROLE }}\n          SNOWFLAKE_WAREHOUSE: ${{ secrets.SNOWFLAKE_WAREHOUSE }}\n          SNOWFLAKE_DATABASE: ${{ secrets.SNOWFLAKE_DATABASE }}\n          SNOWFLAKE_SCHEMA: ${{ secrets.SNOWFLAKE_SCHEMA }}\n        run: |\n          python scripts/deploy_notebooks.py DEMO_DB PROD_SCHEMA NOTEBOOK_PIPELINES ./notebooks\n          python scripts/deploy_task_dag.py DEMO_DB PROD_SCHEMA NOTEBOOK_PIPELINES\n```\n\nWe're running two Python scripts for the deployment:\n\n1. **deploy_notebooks.py**: This script uploads the notebook files to a temporary stage and creates (or updates) the Notebook Project Object in the `PROD_SCHEMA`. It uses the Snowpark Python API to interact with Snowflake.\n\n2. **deploy_task_dag.py**: This script creates the Task DAG using the Python Task DAG API. Each task calls `EXECUTE NOTEBOOK PROJECT` to run the appropriate notebook from our NPO.\n\nNotice that the scripts use environment variables for Snowflake credentials, which are populated from GitHub Secrets. This keeps your credentials secure and out of your code.\n\n### Executing the Production DAG\n\nThe GitHub Actions deployment pipeline just deployed the production version of both your Notebook Project object (which contains the actual notebook files) and your Task DAG, into the `PROD_SCHEMA`. The final step here is optional, but if you want to actually run the production version of your Notebooks you'll need to manually execute the production version of the Task DAG as follows:\n\n1. In the Snowsight navigation menu, click **Catalog** » **Database Explorer**\n2. In the **Database Explorer** pane, navigate to the `DEMO_DB` database and `PROD_SCHEMA` schema\n3. For the selected schema, select and expand **Tasks**\n4. Select the root `DEMO_DAG` task\n5. Select the **Graph** tab\n6. Click on the \"Run Task Graph\" play button above the diagram (and if not already set, you may have to pick a warehouse to execute)\n\nAlternatively, you can run the DAG manually using SQL:\n\n```sql\nUSE ROLE DEMO_ROLE;\nEXECUTE TASK DEMO_DB.PROD_SCHEMA.DEMO_DAG;\n```\n\n\n\u003C!-- ------------------------ --\u003E\n## Teardown\n\nOnce you're finished with the Quickstart and want to clean things up, toggle back to the `00_start_here` Notebook and scroll down to the \"Step 08 Teardown\" section. Then just run the SQL commands in the `sql_step08_teardown` cell to remove all the objects created during the Quickstart.\n\nFinally, if you want, you can also delete the demo Workspace you created and the forked copy of the repository in your GitHub account.\n\n\u003C!-- ------------------------ --\u003E\n## Conclusion And Resources\n\nCongratulations! You have now built end-to-end data engineering pipelines with Notebooks in Snowflake. You've also seen how to follow a complete Software Development Life Cycle (SDLC) for data engineering with Notebooks, including integration with Git, deploying to multiple environments through a CI/CD pipeline, instrumenting your code for monitoring and debugging, and orchestrating the pipelines with Task DAGs. Here's a quick visual recap:\n\n![assets/quickstart_overview.png](https://www.snowflake.com/content/dam/snowflake-site/developers/guides/data-engineering-with-notebooks/quickstart_overview.png?v=df037233)\n\nHopefully you now have the building blocks, and examples, you need to get started building your own data engineering pipelines with Notebooks. So, what will you build now?\n\n### What You Learned\n* How to ingest custom file formats (like Excel) with Snowpark from an external stage (such as an S3 bucket) into a Snowflake table\n* How to access data from Snowflake Marketplace and use it for your analysis\n* How to use Snowflake Notebooks and the Snowpark DataFrame API to build data engineering pipelines\n* How to add logging to your Python data engineering code and monitor from within Snowsight\n* How to use the Snowflake Python Management API to programmatically work with Snowflake objects\n* How to use the Python Task DAG API to programmatically manage Snowflake Tasks\n* How to use Cortex Code to accelerate data engineering development directly in Snowsight\n* How to build CI/CD pipelines using Snowflake's Git Integration, the Snowflake CLI, and GitHub Actions\n* How to deploy Snowflake Notebooks from dev to production\n\n### Related Resources\n* [Source Code on GitHub](https://github.com/Snowflake-Labs/sfguide-data-engineering-with-notebooks)\n* [Data Engineering Pipelines with Snowpark Python](/en/developers/guides/data-engineering-pipelines-with-snowpark-python/) (Advanced Quickstart)\n* [Snowflake Notebooks in Workspaces](https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-overview)\n* [Run and Schedule Notebooks in Workspaces](https://docs.snowflake.com/en/user-guide/ui-snowsight/notebooks-in-workspaces/notebooks-in-workspaces-schedule)\n* [Git-integrated Workspaces](https://docs.snowflake.com/en/user-guide/ui-snowsight/workspaces-git)\n* [Snowflake CLI](https://docs.snowflake.com/en/developer-guide/snowflake-cli/index)\n* [Snowflake Python Management API](https://docs.snowflake.com/en/developer-guide/snowflake-python-api/snowflake-python-overview)\n* [Download Reference Architecture](https://github.com/Snowflake-Labs/sfquickstarts/blob/master/site/sfguides/src/data-engineering-with-notebooks/assets/quickstart_overview.png)\n","multiValue":false,":type":"text/x-markdown"},"quickstartArticleLogoImage":{"dataType":"string","title":"Quickstart Article Logo Image","multiValue":false,":type":"text/plain"}},"elementsOrder":["quickstartArticleBody","quickstartArticleLogoImage"],"model":"snowflake-site/models/quickstart-article"},"flexible_column_cont":{"id":"flexible-column-container-54471e5442","type":"2-column-75-25","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"none","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-0bb53b3512",":items":{"quickstart_last_modi":{"id":"quickstart-last-modified-a6d98cfb94","icon":{"id":"icon","icon":"calendar",":type":"snowflake-site/components/icon","appliedCssClassNames":"snowflake-icon-blue"},"lastModifiedDatePrefix":"Updated","lastModifiedDate":"2026-06-18",":type":"snowflake-site/components/quickstart/quickstart-last-modified","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"},"text":{"id":"text-5423f7d39c","additionalClasses":"qs-disclaimer-text","text":"\u003Cp\u003E\u003Cspan style=\"color: #666;\"\u003EThis content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake instances\u003C/span\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"snowflake-responsive-component-top-padding-small"}},":itemsOrder":["quickstart_last_modi","text"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-463a42677f",":items":{},":itemsOrder":[],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false}},":itemsOrder":["contentfragment","flexible_column_cont"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-8413abb984",":items":{"quickstart_table_of_":{"layout":"SIMPLE","id":"container-b51ee30dd3","isDeveloperGuidesPage":false,":items":{"quickstart_table_of_":{"id":"quickstart-table-of-content-30d32f1e6c",":type":"snowflake-site/components/quickstart/quickstart-table-of-content","fragmentPath":"/content/dam/snowflake-site/en/content-fragments/quickstarts/data-engineering-with-notebooks","headings":["\u003Ch2\u003EOverview\u003C/h2\u003E","\u003Ch2\u003EQuickstart Setup\u003C/h2\u003E","\u003Ch2\u003ESetup Snowflake\u003C/h2\u003E","\u003Ch2\u003ELoad Weather\u003C/h2\u003E","\u003Ch2\u003ELoad Excel Files\u003C/h2\u003E","\u003Ch2\u003ELoad Daily City Metrics\u003C/h2\u003E","\u003Ch2\u003EUsing Cortex Code\u003C/h2\u003E","\u003Ch2\u003EDeploy Notebook Project to Dev\u003C/h2\u003E","\u003Ch2\u003EOrchestrate Pipelines\u003C/h2\u003E","\u003Ch2\u003EDeploy to Production\u003C/h2\u003E","\u003Ch2\u003ETeardown\u003C/h2\u003E","\u003Ch2\u003EConclusion And Resources\u003C/h2\u003E"]},"quickstart_button":{"id":"quickstart-button-df46fd1bff",":type":"snowflake-site/components/quickstart/quickstart-button","fragmentPath":"/content/dam/snowflake-site/en/content-fragments/quickstarts/data-engineering-with-notebooks","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"}},":itemsOrder":["quickstart_table_of_","quickstart_button"],":type":"snowflake-site/components/quickstart/quickstart-table-of-content/quickstart-table-of-content-container"}},":itemsOrder":["quickstart_table_of_"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false},"markup_editor":{"id":"markup-editor-ed0e1acbdd","title":"Page CSS","cssContent":"#quickstart-template-main-flexible-container{padding:24px}#quickstart-template-main-flexible-container \u003E .snowflake-flexible-column-container-items{grid-template-columns:1fr 0}.qs-disclaimer-text p \u003E span{font-size:15px !important}@media (min-width:768px){#quickstart-template-main-flexible-container{padding:24px 32px}#quickstart-template-main-flexible-container \u003E .snowflake-flexible-column-container-items{grid-template-columns:7fr 3fr;gap:48px}}@media (max-width:767px){#quickstart-template-main-flexible-container \u003E .snowflake-flexible-column-container-items{gap:0}}@media (min-width:1024px){#quickstart-template-main-flexible-container{padding:0 92px 48px 92px}#quickstart-template-main-flexible-container \u003E .snowflake-flexible-column-container-items{gap:117px}}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"}},":itemsOrder":["quickstart_hero","flexible_column_cont","markup_editor"],":type":"wcm/foundation/components/responsivegrid"},"modal_container":{"layout":"SIMPLE","id":"container-ec1ef413ec",":items":{},":itemsOrder":[],":type":"snowflake-site/components/modal/modal-container"},"experiencefragment-footer":{"id":"experiencefragment-74efe3fb26","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/footer/master/jcr:content","configured":true,":items":{"root":{"additionalClasses":"sf-footer","layout":"SIMPLE","id":"container-1cc18c7bc6",":items":{"container_copy":{"additionalClasses":"sf-footer__inner","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-6742e835b0",":items":{"flexible_column_cont":{"id":"flexible-column-container-0e6ed1b52e","type":"1-column","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"medium","bottomPadding":"extra-small","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"sf-footer-grid","backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-517e334151",":items":{"container":{"additionalClasses":"sf-footer-grid__inner","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","container_1622723482":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-2d23281d69",":items":{"container_1622723482":{"additionalClasses":"sf-footer__column","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-4b9d3a9e5e",":items":{"container":{"additionalClasses":"sf-footer__newsletter-group","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12","marketo_v2":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-7e821e84b2",":items":{"text":{"id":"text-d51296b53f","additionalClasses":"sf-footer__newsletter-title","text":"\u003Cp\u003E\u003Cb\u003ESubscribe to our monthly newsletter\u003C/b\u003E\u003C/p\u003E\r\n\u003Cp\u003EStay up to date on Snowflake’s latest products, expert insights and resources—right in your inbox!\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-04"},"marketo_v2":{"id":"marketo-v2-1db53a05f1","marketoForm":{"successUrl":null,"edit":false,"formId":"45871","script":null,"hidden":null,"values":null},"munchkinId":"252-RFO-227","serverInstance":"252-RFO-227.mktoweb.com","marketoConfigured":true,"formConfigured":true,":type":"snowflake-site/components/form/marketo-v2"}},":itemsOrder":["text","marketo_v2"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"}},":itemsOrder":["container"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"},"container":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"text_copy":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-72bfc54cae",":items":{"text":{"id":"text-64ffa66ad3","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003EProduct\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/platform/\"\u003EPlatform\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/product/snowflake-cowork/\"\u003ESnowflake CoWork\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/data-engineering/\"\u003EData Engineering\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/analytics/\"\u003EAnalytics\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/ai/\"\u003EAI\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/product/applications-and-collaboration/\"\u003EApplications & Collaboration\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/pricing-options/\"\u003EPricing\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"},"text_copy":{"id":"text-d5e7d08d5a","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003ESupport\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/support/\"\u003ESupport\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/legal/addenda/priority-support-services-description/\"\u003EPriority Support\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://status.snowflake.com/\" target=\"_blank\" rel=\"noopener noreferrer\"\u003EStatus\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"}},":itemsOrder":["text","text_copy"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":type":"snowflake-site/components/container"},"container_copy_copy":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-46522ce7ab",":items":{"text":{"id":"text-75f3c83b5f","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003E\u003Ca href=\"/en/solutions/industries/\"\u003EIndustries\u003C/a\u003E\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/advertising-media-entertainment/\"\u003EAdvertising, Media & Entertainment\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/financial-services/\"\u003EFinancial Services\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/healthcare-and-life-sciences/\"\u003EHealthcare & Life Sciences\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/manufacturing/\"\u003EManufacturing\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/public-sector/\"\u003EPublic Sector\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/retail-consumer-goods/\"\u003ERetail & Consumer Goods\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/solutions/industries/telecom/\"\u003ETelecom\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/solutions/industries/technology/\"\u003ETechnology\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"}},":itemsOrder":["text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"},"container_copy":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-783afd7d3c",":items":{"text":{"id":"text-52d3ba237a","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003ECompany\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/about-snowflake/\"\u003EAbout Snowflake\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/leadership-and-board/\"\u003ELeadership & Board\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://careers.snowflake.com/us/en\" target=\"_blank\" rel=\"noopener noreferrer\"\u003ECareers\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://investors.snowflake.com/overview/default.aspx\" target=\"_blank\" rel=\"noopener noreferrer\"\u003EInvestor Relations\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://trust.snowflake.com/\" target=\"_blank\" rel=\"noopener noreferrer\"\u003ETrust Center\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/brand-guidelines/\" target=\"_blank\" rel=\"noopener noreferrer\"\u003EBrand Guidelines\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/contact/\"\u003EContact\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/news/\"\u003ENewsroom\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/esg/\"\u003EEnvironmental, Social & Governance\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/snowflake-ventures/\"\u003ESnowflake Ventures\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/end-data-disparity/\"\u003EEnd Data Disparity\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/summit/\"\u003ESnowflake Summit 26\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"}},":itemsOrder":["text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"},"container_copy_copy_":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-98bd1f3d11",":items":{"text":{"id":"text-ea8ceaf0b4","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003ELearn\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://snowflake.com/en/resources/\"\u003EResource Library\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/webinars/demo/\"\u003ELive Demos\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/fundamentals/\"\u003EFundamentals\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/resources/learn/training/\"\u003ETraining\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/resources/learn/certifications/\"\u003ECertifications\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://learn.snowflake.com/en/\"\u003ESnowflake University\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/developers/guides\"\u003EDeveloper Guides\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/\"\u003EDocumentation\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/data-governance/\"\u003EData Governance\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"}},":itemsOrder":["text"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"}},":itemsOrder":["container_1622723482","container","container_copy_copy","container_copy","container_copy_copy_"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"}},":itemsOrder":["container"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false}},":itemsOrder":["flexible_column_cont"],"appliedCssClassNames":"snowflake-container snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"},"container_573483281_":{"additionalClasses":"sf-footer__bottom","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container_112062425":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-cb5850400d",":items":{"container_112062425":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-4bff0d3cb2",":items":{"flexible_column_cont":{"id":"flexible-column-container-9554d4ce56","type":"1-column","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"none","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-71f94c3d26",":items":{"container":{"additionalClasses":"sf-footer__legal-container","gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","text_copy_copy_16360":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-ce52d02fc8",":items":{"container":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"image":"aem-GridColumn aem-GridColumn--default--12"},"layout":"RESPONSIVE_GRID","columnCount":12,"id":"container-8a89bcdc64",":items":{"image":{"id":"image-aca92bd754","additionalClasses":"sf-footer__logo","imageLink":{"valid":true,"url":"/en/"},"lazyEnabled":true,"alt":"Snowflake logo","src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/en/site/footer/master/_jcr_content/root/container_573483281_/container_112062425/flexible_column_cont/flexible_column_content_container_1/container/container/image.coreimg.svg/1747882370694/nav-icon-snowflake-bug.svg",":type":"snowflake-site/components/image"}},":itemsOrder":["image"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":type":"snowflake-site/components/container"},"text_copy_copy_16360":{"id":"text-63b9b5cb4f","additionalClasses":"sf-footer__legal-links","text":"\u003Cul\u003E\r\n\u003Cli\u003E© 2026 Snowflake Inc. All Rights Reserved\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/legal/privacy/privacy-policy/\"\u003EPrivacy Policy\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://snowflake.com/en/legal/snowflake-site-terms/\"\u003ESite Terms\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://info.snowflake.com/Preference-center.html\"\u003ECommunication Preferences\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Cbutton id=\"ot-sdk-btn\" class=\"ot-sdk-show-settings\"\u003ECookie Settings\u003C/button\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/legal/privacy/privacy-policy/#12\"\u003EDo Not Share My Personal Information\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/legal/\"\u003ELegal\u003C/a\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"},"markup_editor":{"id":"markup-editor-6a4d5f6683","title":" ","htmlContent":"\u003Cdiv class=\"sf-footer__social\"\u003E\r\n\u003Cdiv data-testid=\"snowflake-footer-twitter\" class=\"snowflake-button-icon snowflake-button-white snowflake-footer-social-item\"\u003E\u003Cdiv class=\"snowflake-button-icon \"\u003E\u003Ca href=\"https://x.com/Snowflake\" data-testid=\"button-external\" aria-label=\"X (Twitter)\" role=\"button\" class=\"snowflake-button-container\" title=\"X (Twitter)\" tabindex=\"0\" target=\"_blank\" rel=\"noreferrer\"\u003E\u003Cdiv data-testid=\"button-icon-wrapper\"\u003E\u003Csvg xmlns=\"http://www.w3.org/2000/svg\" fill=\"none\" viewBox=\"0 0 59 53\" class=\"button-icon\"\u003E\u003Cpath fill=\"currentColor\" d=\"M46.614 0h9.044L35.8 22.49 59 53H40.795L26.54 34.46 10.223 53H1.18l21.036-24.055L0 0h18.657l12.878 16.937zM43.45 47.72h5.013L16.023 5.085h-5.387z\"\u003E\u003C/path\u003E\u003C/svg\u003E\u003C/div\u003E\u003C/a\u003E\u003Cdiv\u003E\u003C/div\u003E\u003C/div\u003E\u003C/div\u003E\u003Cdiv data-testid=\"snowflake-footer-linkedin\" class=\"snowflake-button-icon snowflake-button-white snowflake-footer-social-item\"\u003E\u003Cdiv class=\"snowflake-button-icon \"\u003E\u003Ca href=\"https://www.linkedin.com/company/3653845\" data-testid=\"button-external\" aria-label=\"LinkedIn\" role=\"button\" class=\"snowflake-button-container\" title=\"LinkedIn\" tabindex=\"0\" target=\"_blank\" rel=\"noreferrer\"\u003E\u003Cdiv data-testid=\"button-icon-wrapper\"\u003E\u003Csvg xmlns=\"http://www.w3.org/2000/svg\" fill=\"currentColor\" viewBox=\"0 0 24 24\" class=\"button-icon\"\u003E\u003Cpath d=\"M22.223 0H1.772C.792 0 0 .773 0 1.73v20.536C0 23.222.792 24 1.772 24h20.451c.98 0 1.777-.778 1.777-1.73V1.73C24 .773 23.203 0 22.223 0ZM7.12 20.452H3.558V8.995H7.12v11.457ZM5.34 7.434a2.064 2.064 0 1 1 0-4.125 2.063 2.063 0 0 1 0 4.125Zm15.112 13.018h-3.558v-5.57c0-1.326-.024-3.037-1.852-3.037-1.851 0-2.133 1.449-2.133 2.944v5.663H9.356V8.995h3.413v1.566h.047c.473-.9 1.636-1.852 3.365-1.852 3.605 0 4.27 2.372 4.27 5.457v6.286Z\"\u003E\u003C/path\u003E\u003C/svg\u003E\u003C/div\u003E\u003C/a\u003E\u003Cdiv\u003E\u003C/div\u003E\u003C/div\u003E\u003C/div\u003E\u003Cdiv data-testid=\"snowflake-footer-facebook\" class=\"snowflake-button-icon snowflake-button-white snowflake-footer-social-item\"\u003E\u003Cdiv class=\"snowflake-button-icon \"\u003E\u003Ca href=\"https://www.facebook.com/snowflakedb/\" data-testid=\"button-external\" aria-label=\"Facebook\" role=\"button\" class=\"snowflake-button-container\" title=\"Facebook\" tabindex=\"0\" target=\"_blank\" rel=\"noreferrer\"\u003E\u003Cdiv data-testid=\"button-icon-wrapper\"\u003E\u003Csvg xmlns=\"http://www.w3.org/2000/svg\" fill=\"currentColor\" viewBox=\"0 0 24 24\" class=\"button-icon\"\u003E\u003Cpath d=\"M24 12c0-6.627-5.373-12-12-12S0 5.373 0 12c0 5.99 4.388 10.954 10.125 11.854V15.47H7.078V12h3.047V9.356c0-3.007 1.792-4.668 4.533-4.668 1.312 0 2.686.234 2.686.234v2.953H15.83c-1.491 0-1.956.925-1.956 1.875V12h3.328l-.532 3.469h-2.796v8.385C19.612 22.954 24 17.99 24 12Z\"\u003E\u003C/path\u003E\u003C/svg\u003E\u003C/div\u003E\u003C/a\u003E\u003Cdiv\u003E\u003C/div\u003E\u003C/div\u003E\u003C/div\u003E\u003Cdiv data-testid=\"snowflake-footer-youtube\" class=\"snowflake-button-icon snowflake-button-white snowflake-footer-social-item\"\u003E\u003Cdiv class=\"snowflake-button-icon \"\u003E\u003Ca href=\"https://www.youtube.com/user/snowflakecomputing\" data-testid=\"button-external\" aria-label=\"YouTube\" role=\"button\" class=\"snowflake-button-container\" title=\"YouTube\" tabindex=\"0\" target=\"_blank\" rel=\"noreferrer\"\u003E\u003Cdiv data-testid=\"button-icon-wrapper\"\u003E\u003Csvg xmlns=\"http://www.w3.org/2000/svg\" fill=\"currentColor\" viewBox=\"0 0 24 24\" class=\"button-icon\"\u003E\u003Cpath d=\"M23.76 7.2s-.233-1.655-.955-2.381c-.914-.956-1.936-.961-2.405-1.017-3.356-.244-8.395-.244-8.395-.244h-.01s-5.039 0-8.395.244c-.469.056-1.49.06-2.405 1.017C.473 5.545.244 7.2.244 7.2S0 9.145 0 11.086v1.819c0 1.94.24 3.886.24 3.886s.233 1.654.95 2.38c.915.957 2.115.924 2.65 1.027 1.92.183 8.16.24 8.16.24s5.044-.01 8.4-.249c.469-.056 1.49-.06 2.405-1.017.722-.727.956-2.381.956-2.381S24 14.85 24 12.905v-1.819c0-1.94-.24-3.886-.24-3.886ZM9.52 15.113V8.367l6.483 3.385-6.483 3.36Z\"\u003E\u003C/path\u003E\u003C/svg\u003E\u003C/div\u003E\u003C/a\u003E\u003Cdiv\u003E\u003C/div\u003E\u003C/div\u003E\u003C/div\u003E\r\n\u003C/div\u003E","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"}},":itemsOrder":["container","text_copy_copy_16360","markup_editor"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-none",":type":"snowflake-site/components/container"}},":itemsOrder":["container"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false}},":itemsOrder":["flexible_column_cont"],"appliedCssClassNames":"snowflake-container snowflake-responsive-container-inner-padding-small",":type":"snowflake-site/components/container"}},":itemsOrder":["container_112062425"],"appliedCssClassNames":"snowflake-responsive-container-inner-padding-none",":type":"snowflake-site/components/container"},"markup_editor_copy":{"id":"markup-editor-e0184f8998","title":"New css","cssContent":".snowflake-image-container img{background-color:transparent}div.snowflake-person-chip-avatar{width:80px !important}#snowflake-blog-template-main-container .aem-GridColumn:has(.vertical-video){background-color:#000;border-radius:16px;overflow:hidden}#snowflake-blog-template-main-container .vertical-video{max-width:240px;margin-left:auto;margin-right:auto}@media screen and (min-width:1367px){.dynamic .heading-1-v2 .snowflake-title-v2-line{font-size:72px !important;line-height:60px !important}}.snowflake-flexible-column-container-items-alignment-match-height .download-card,.snowflake-flexible-column-container-items-alignment-match-height .download-card\u003E.container{height:100%}.download-card div.code-toolbar\u003E.toolbar .copy-to-clipboard-button{background-color:white;border:1px solid #a9e1f6;margin-right:4px;top:6px;border-radius:16px;height:26px;width:40px}.download-card .snowflake-code-snippet\u003Ediv.code-toolbar\u003E.toolbar\u003E.toolbar-item\u003Ebutton:before{content:'';background-image:url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='16' height='16' viewBox='0 0 24 24' fill='none' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3E%3Crect x='9' y='9' width='13' height='13' rx='2' ry='2' style='stroke:%23249EDC;'%3E%3C/rect%3E%3Cpath d='M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1' style='stroke:%23249EDC;'%3E%3C/path%3E%3C/svg%3E\");background-size:auto 65%;background-position:center;background-repeat:no-repeat;top:0;left:0;width:100%;height:100%}.download-card .snowflake-code-snippet\u003Ediv.code-toolbar\u003E.toolbar\u003E.toolbar-item\u003Ebutton:hover:before{background-image:url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='16' height='16' viewBox='0 0 24 24' fill='none' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'%3E%3Crect x='9' y='9' width='13' height='13' rx='2' ry='2' style='stroke:%23fff;'%3E%3C/rect%3E%3Cpath d='M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1' style='stroke:%23fff;'%3E%3C/path%3E%3C/svg%3E\")}.download-card\u003Ediv{background-color:#fff;border:1px solid #ccc;border-radius:8px;padding:24px}.download-chip__headline{border-bottom:1px solid #ccc;padding-bottom:16px;margin-bottom:16px}.download-chip{padding:8px 12px !important;border-radius:4px;transition:300ms ease background-color}.download-chip .black-blue-text-color .snowflake-title-v2-line{color:#000 !important;padding-right:24px;font-family:'Lato',sans-serif;font-size:14px !important;font-weight:500 !important}.download-chip .black-blue-text-color .snowflake-title-v2-line:not(:first-child){opacity:.6;font-style:italic !important}.download-chip .snowflake-content-chip-button{display:none}.download-chip.is-external-link{background-size:16px 16px;background-image:url(\"data:image/svg+xml,%3Csvg width='15' height='15' viewBox='0 0 15 15' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M1.06055 13.0607L11.8605 2.26067M13.0605 10.6607V1.06067H3.46055' stroke='%23249EDC' stroke-width='2.12132' stroke-linecap='round' stroke-linejoin='round'/%3E%3C/svg%3E%0A\")}.download-chip{background-image:url(\"data:image/svg+xml,%3Csvg width='18' height='18' viewBox='0 0 18 18' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cg clip-path='url(%23clip0_883_7979)'%3E%3Cpath d='M3.375 16.875H14.625' stroke='%23249EDC' stroke-width='1.40625' stroke-linecap='round' stroke-linejoin='round'/%3E%3Cpath d='M9 1.125V11.25' stroke='%23249EDC' stroke-width='1.40625' stroke-linecap='round' stroke-linejoin='round'/%3E%3Cpath d='M4.5 7.875L9 12.375L13.5 7.875' stroke='%23249EDC' stroke-width='1.40625' stroke-linecap='round' stroke-linejoin='round'/%3E%3C/g%3E%3Cdefs%3E%3CclipPath id='clip0_883_7979'%3E%3Crect width='18' height='18' fill='white'/%3E%3C/clipPath%3E%3C/defs%3E%3C/svg%3E%0A\");background-size:24px auto;background-repeat:no-repeat;background-position:calc(100% - 12px) center}.download-chip__headline{display:flex;gap:16px;flex-direction:row !important;flex-wrap:nowrap}.download-chip__headline::before{content:'';display:inline-block;width:24px;height:24px;background-position:center;background-image:url(\"data:image/svg+xml,%3Csvg width='21' height='21' viewBox='0 0 21 21' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7.50005 9.89999C8.13657 9.89999 8.74702 9.64713 9.19711 9.19704C9.64719 8.74696 9.90005 8.13651 9.90005 7.49999V2.69999C9.90005 2.06347 9.64719 1.45302 9.19711 1.00293C8.74702 .552844 8.13657 .299988 7.50005 .299988H2.70005C2.06353 .299988 1.45308 .552844 1.00299 1.00293C.552905 1.45302 .300049 2.06347 .300049 2.69999V7.49999C.300049 8.13651 .552905 8.74696 1.00299 9.19704C1.45308 9.64713 2.06353 9.89999 2.70005 9.89999H7.50005ZM7.50005 7.49999H2.70005V2.69999H7.50005V7.49999Z' fill='%23249EDC' stroke='white' stroke-width='.6'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7.50005 20.3C8.13657 20.3 8.74702 20.0472 9.19711 19.5971C9.64719 19.147 9.90005 18.5365 9.90005 17.9V13.1C9.90005 12.4635 9.64719 11.853 9.19711 11.403C8.74702 10.9529 8.13657 10.7 7.50005 10.7H2.70005C2.06353 10.7 1.45308 10.9529 1.00299 11.403C.552905 11.853 .300049 12.4635 .300049 13.1V17.9C.300049 18.5365 .552905 19.147 1.00299 19.5971C1.45308 20.0472 2.06353 20.3 2.70005 20.3H7.50005ZM7.50005 17.9H2.70005V13.1H7.50005V17.9Z' fill='%23249EDC' stroke='white' stroke-width='.6'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M17.9001 9.89999C18.5366 9.89999 19.147 9.64713 19.5971 9.19704C20.0472 8.74696 20.3001 8.13651 20.3001 7.49999V2.69999C20.3001 2.06347 20.0472 1.45302 19.5971 1.00293C19.147 .552844 18.5366 .299988 17.9001 .299988H13.1001C12.4636 .299988 11.8531 .552844 11.403 1.00293C10.9529 1.45302 10.7001 2.06347 10.7001 2.69999V7.49999C10.7001 8.13651 10.9529 8.74696 11.403 9.19704C11.8531 9.64713 12.4636 9.89999 13.1001 9.89999H17.9001ZM17.9001 7.49999H13.1001V2.69999H17.9001V7.49999Z' fill='%23249EDC' stroke='white' stroke-width='.6'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M17.9001 20.3C18.5366 20.3 19.147 20.0472 19.5971 19.5971C20.0472 19.147 20.3001 18.5365 20.3001 17.9V13.1C20.3001 12.4635 20.0472 11.853 19.5971 11.403C19.147 10.9529 18.5366 10.7 17.9001 10.7H13.1001C12.4636 10.7 11.8531 10.9529 11.403 11.403C10.9529 11.853 10.7001 12.4635 10.7001 13.1V17.9C10.7001 18.5365 10.9529 19.147 11.403 19.5971C11.8531 20.0472 12.4636 20.3 13.1001 20.3H17.9001ZM17.9001 17.9H13.1001V13.1H17.9001V17.9Z' fill='%23249EDC' stroke='white' stroke-width='.6'/%3E%3C/svg%3E%0A\");background-size:contain;background-repeat:no-repeat}.download-chip__headline.is-cli::before{background-image:url(\"data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M4 17L10 11L4 5' stroke='%23000' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/%3E%3Cpath d='M12 19H20' stroke='%23000' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/%3E%3C/svg%3E%0A\")}.download-card pre[class*=language-]{padding:8px 12px;background-color:var(--ui-background-05);overflow:hidden}.download-chip__headline.is-windows,.download-chip__headline.is-mac{gap:12px}.download-chip__headline.is-windows::before{width:16px;height:20px;background-image:url(\"data:image/svg+xml,%3Csvg width='4875' height='4875' viewBox='0 0 4875 4875' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cg clip-path='url(%23clip0_122_201)'%3E%3Cpath d='M0 0H2311V2310H0V0ZM2564 0H4875V2310H2564V0ZM0 2564H2311V4875H0V2564ZM2564 2564H4875V4875H2564' fill='%23000'/%3E%3C/g%3E%3C/svg%3E\")}.download-chip__headline.is-mac::before{width:16px;height:20px;background-image:url(\"data:image/svg+xml,%3Csvg version='1.1' id='Layer_1' xmlns:x='ns_extend;' xmlns:i='ns_ai;' xmlns:graph='ns_graphs;' xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' x='0' y='0' viewBox='0 0 41.5 51' style='enable-background:new 0 0 41.5 51;' xml:space='preserve'%3E%3Cmetadata%3E%3Csfw xmlns='ns_sfw;'%3E%3Cslices%3E%3C/slices%3E%3CsliceSourceBounds bottomLeftOrigin='true' height='51' width='41.5' x='166.1' y='-208.1'%3E%3C/sliceSourceBounds%3E%3C/sfw%3E%3C/metadata%3E%3Cg%3E%3Cpath d='M40.2,17.4c-3.4,2.1-5.5,5.7-5.5,9.7c0,4.5,2.7,8.6,6.8,10.3c-.8,2.6-2,5-3.5,7.2c-2.2,3.1-4.5,6.3-7.9,6.3s-4.4-2-8.4-2 c-3.9,0-5.3,2.1-8.5,2.1s-5.4-2.9-7.9-6.5C2,39.5,.1,33.7,0,27.6c0-9.9,6.4-15.2,12.8-15.2c3.4,0,6.2,2.2,8.3,2.2 c2,0,5.2-2.3,9-2.3C34.1,12.2,37.9,14.1,40.2,17.4z M28.3,8.1C30,6.1,30.9,3.6,31,1c0-.3,0-.7-.1-1c-2.9,.3-5.6,1.7-7.5,3.9 c-1.7,1.9-2.7,4.3-2.8,6.9c0,.3,0,.6,.1,.9c.2,0,.5,.1,.7,.1C24.1,11.6,26.6,10.2,28.3,8.1z'%3E%3C/path%3E%3C/g%3E%3C/svg%3E\")}.download-chip__headline.is-desktop::before{background-image:url(\"data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cg opacity='.8'%3E%3Cpath d='M1.5 21H22.5V18H1.5V21Z' fill='%23000' stroke='white' stroke-width='.75'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M19.5 15C20.2956 15 21.0587 14.6839 21.6213 14.1213C22.1839 13.5587 22.5 12.7956 22.5 12V6C22.5 5.20435 22.1839 4.44129 21.6213 3.87868C21.0587 3.31607 20.2956 3 19.5 3H4.5C3.70435 3 2.94129 3.31607 2.37868 3.87868C1.81607 4.44129 1.5 5.20435 1.5 6V12C1.5 12.7956 1.81607 13.5587 2.37868 14.1213C2.94129 14.6839 3.70435 15 4.5 15H19.5ZM19.5 12H4.5V6H19.5V12Z' fill='%23000' stroke='white' stroke-width='.75'/%3E%3C/g%3E%3C/svg%3E%0A\")}.download-card .snowflake-code-snippet,.download-card .snowflake-code-snippet code,.download-card .snowflake-code-snippet pre{font-size:14px;color:#000;text-shadow:none !important}.download-chip:hover{background-color:var(--ui-background-05) !important;transition:300ms ease background-color}body:has(.snowflake-skip-to-content[style]) #subNav,.pushdown-banner-dismissed #subNav{top:var(--scroll-padding-top) !important;transition:300ms ease top}body:has(.snowflake-skip-to-content[style*=\"58\"]) #subNav{top:34px !important}body:has(.snowflake-skip-to-content[style*=\"82\"]) #subNav{top:58px !important}body:has(.snowflake-skip-to-content[style*=\"130\"]) #subNav{top:106px !important}body:has(.snowflake-skip-to-content[style*=\"138\"]) #subNav{top:114px !important}body:has(.snowflake-skip-to-content[style*=\"146\"]) #subNav{top:122px !important}.is-hidden .snowflake-person-chip-avatar{display:none}.is-small .snowflake-person-chip-avatar{width:56px;height:56px}.ai-summary ul{margin:16px 0 0 0 !important;padding:0 !important;list-style-type:none}.ai-summary li{margin:0;padding:0 0 0 32px;position:relative}.ai-summary li::before{content:\"\";display:block;border-radius:100%;background:#29b5e8;width:18px;height:18px;position:absolute;top:4px;left:0;border:5px solid #e5f2f7;box-sizing:border-box}.ai-summary li:not(:last-child){margin-bottom:1rem}.snowflake-content-chip-image__image{aspect-ratio:5 / 3 !important}.content-chip-new .snowflake-content-chip-image__image{height:100% !important;aspect-ratio:unset !important}.snapshot-card .snowflake-text p:not(:first-child){margin-top:var(--spacing-01)}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(2) p:has(b){font-family:'Texta',sans-serif;margin-top:24px}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(2) p b{font-weight:700 !important}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(2){border-bottom:1px solid #ccc;padding-bottom:24px}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(3) p:first-child:has(b){font-family:'Texta',sans-serif;font-size:20px !important;margin-bottom:1rem !important}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(3) li{display:inline-block}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(3) li a{display:inline-block;text-decoration:none;padding:4px 16px !important;border:1px solid #ccc;border-radius:24px;color:#666 !important}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(3) ul{list-style-type:none;display:flex;padding:0 !important;margin:0 !important;gap:12px}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container img{width:90%;max-width:240px;margin:0 auto}.snapshot-card\u003E.container\u003E.cmp-container\u003E.aem-container{padding:40px;max-width:450px;margin:0 0 0 auto;background-color:#fff;box-shadow:0 2px 6px 0 rgba(152,162,179,.25),0 10px 20px 0 rgba(152,162,179,.10);border-radius:8px;border-top:4px solid var(--ui-01)}.ai-summary{background-color:#f3fbfe;border-left:2px solid var(--ui-01);padding:40px}.ai-summary\u003Espan p:last-child:has(i){color:#666;font-size:14px !important}.ai-summary\u003Espan p:last-child:has(i) a{color:#666 !important;text-decoration:underline !important}.ai-summary\u003Espan p:last-child:has(i) a:hover{color:var(--ui-01) !Important}.ai-summary\u003Espan p:first-child:has(b)::after{content:'';display:inline-block;width:20px;height:20px;background-image:url(\"data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9.3158 3.15226C8.6475 6.2258 6.22698 8.64545 3.15232 9.31587C2.94923 9.36072 2.94923 9.63928 3.15232 9.68413C6.22698 10.3522 8.6475 12.7742 9.3158 15.8477C9.36067 16.0508 9.63933 16.0508 9.6842 15.8477C10.3525 12.7742 12.773 10.3545 15.8477 9.68413C16.0508 9.63928 16.0508 9.36072 15.8477 9.31587C12.773 8.64781 10.3525 6.2258 9.6842 3.15226C9.63933 2.94925 9.36067 2.94925 9.3158 3.15226Z' fill='%23249EDC'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M17.3725 11.5461C16.9098 13.6739 15.2341 15.3491 13.1054 15.8132C12.9649 15.8443 12.9649 16.0371 13.1054 16.0681C15.2341 16.5307 16.9098 18.2074 17.3725 20.3353C17.4035 20.4758 17.5965 20.4758 17.6275 20.3353C18.0902 18.2074 19.7659 16.5323 21.8946 16.0681C22.0352 16.0371 22.0352 15.8443 21.8946 15.8132C19.7659 15.3507 18.0902 13.6739 17.6275 11.5461C17.5965 11.4055 17.4035 11.4055 17.3725 11.5461Z' fill='%23249EDC'/%3E%3C/svg%3E%0A\");background-repeat:no-repeat;background-size:contain;background-position:center;vertical-align:middle;margin-left:8px}.ai-summary\u003Espan p:first-child:has(b){color:var(--ui-01) !important;text-transform:uppercase}.border-top{border-top:1px solid rgba(0,0,0,.2)}.border-top\u003Espan{display:block;padding-top:32px}body .snowflake-card-v2-advanced-image__image{aspect-ratio:16 / 9 !important}.content-chip-new .snowflake-content-chip-image__image{border-radius:0;object-fit:cover;height:100%}.sf-footer #ot-sdk-btn.ot-sdk-show-settings,.sf-footer #ot-sdk-btn.optanon-show-settings{color:rgba(255,255,255,.7) !important;text-underline-offset:4px;border-top:none;border-left:none;border-right:none;border-bottom:1px dotted transparent;background-color:transparent !important;background-image:none !important;transition:300ms ease text-decoration-color;padding:0 !important;font-size:12px;font-family:'Lato',sans-serif}.sf-footer #ot-sdk-btn.ot-sdk-show-settings:hover,.sf-footer #ot-sdk-btn.optanon-show-settings:hover{color:rgba(255,255,255,1) !important;border-bottom:1px dotted var(--ui-01);transition:300ms ease text-decoration-color}.sf-footer__legal-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:last-child{flex-shrink:0}.sf-footer__disclaimers{background-color:#042130}.sf-footer__disclaimers .snowflake-simple-stat-disclaimer p a{color:inherit;text-decoration:none !important}.sf-footer__disclaimers .snowflake-simple-stat-disclaimer p sup{margin-right:2px}.sf-footer__disclaimers .snowflake-simple-stat-disclaimer p{text-indent:-5px;padding-left:5px}.sf-footer__disclaimers-inner{border-top:1px solid rgba(255,255,255,.25);padding:40px 0}.sf-footer__disclaimers .snowflake-simple-stat{align-items:flex-start;text-align:left;color:rgba(255,255,255,.7);margin-bottom:10px}.sf-footer__social{display:flex;justify-content:center;gap:12px}.sf-footer .snowflake-footer-social-item{margin:0 !important}.sf-footer .snowflake-footer-social-item a{line-height:0;background-color:rgba(3,24,35,.8);display:inline-block;width:48px !important;height:48px;border-radius:8px;display:inline-flex;justify-content:center;align-items:center;transition:300ms ease background-color}.sf-footer .snowflake-footer-social-item a:hover{background-color:var(--ui-01) !important;transition:300ms ease background-color}.sf-footer__bottom{padding-bottom:40px}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoError .mktoErrorMsg{max-width:100%;color:#fff}.sf-footer .mktoForm .mktoError .mktoErrorMsg .mktoErrorDetail{display:inline-block}.sf-footer .mktoFormRow:has(.mktoHtmlText:empty){display:none}.sf-footer .mktoFormRow .mktoHtmlText span{color:#fff !important}.sf-footer{background-color:#042130}.sf-footer .optanon-toggle-display:hover{text-decoration-color:var(--ui-01) !important;cursor:pointer !important;text-underline-offset:4px;text-decoration-style:dotted !important;text-decoration-color:var(--ui-01);color:#fff !important;transition:300ms ease text-decoration-color;text-decoration:underline;opacity:1}.sf-footer__logo{width:40px}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container{row-gap:32px}.sf-footer__legal-container\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;justify-content:space-between;align-items:center;text-align:center;row-gap:16px}.sf-footer__legal-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:nth-child(2){text-align:center;flex-grow:1}.sf-footer__legal-links li button,.sf-footer__legal-links li a,.sf-footer__legal-links li{margin:0;color:rgba(255,255,255,.7) !important;font-weight:500}.sf-footer__legal-links li a:hover{color:rgba(255,255,255,1) !important}.sf-footer div.sf-footer__copyright p,.sf-footer div.sf-footer__legal-links li,.sf-footer div.sf-footer__legal-links a,.sf-footer div.sf-footer__legal-links p{font-size:12px !important}.sf-footer__legal-links ul{list-style-type:none;margin:0;padding:0;display:flex;gap:20px;row-gap:4px;justify-content:center;flex-wrap:wrap;text-align:center}.sf-footer__legal-links li:last-child{width:100%}.sf-footer .mktoFormRow:has(.mktoPlaceholder),.sf-footer .mktoFormRow:has(input[type=\"hidden\"]){display:none !important}.sf-footer .mktoFormCol{margin-bottom:0 !important}.sf-footer label[for=\"adhoc1\"]{width:auto !important;flex-grow:1;margin-left:16px}.sf-footer .mktoFieldWrap:has(label[for=\"adhoc1\"]){display:flex;flex-direction:row-reverse;margin-top:22px}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoCheckboxList input[type=checkbox]{background-color:transparent !important;border:1px solid rgba(255,255,255,.4) !important;border-radius:4px !important}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoEmailField,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoTelField,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoTextField,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap select{background-color:transparent !important;color:#fff !important;height:auto !important;border:1px solid rgba(255,255,255,.4) !important;border-radius:4px !important;padding:12px 18px !important}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoEmailField:focus,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoTelField:focus,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoTextField:focus,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap select:focus{border-color:var(--ui-01) !important}.sf-footer .mktoForm *{padding:0 !important}.sf-footer .mktoForm,.sf-footer .snowflake-marketo-form-container{padding:0 !important;background:transparent;margin-bottom:0;box-shadow:none}.sf-footer .mktoHtmlText.mktoHasWidth{width:100% !important;margin:24px 0}.sf-footer .mktoFormRow{flex-direction:column}.sf-footer .mktoForm .mktoButtonWrap{margin:0 !important}.sf-footer select{background-image:url(\"data:image/svg+xml,%3Csvg width='14' height='8' viewBox='0 0 14 8' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M.981445 1.43496L6.90897 7.32496L12.9314 1.33496' stroke='white' stroke-width='1.33333' stroke-miterlimit='10' stroke-linecap='round' stroke-linejoin='round'/%3E%3C/svg%3E%0A\") !important}.sf-footer .snowflake-marketo-form .mktoButtonWrap.mktoNative{justify-content:flex-start}.sf-footer *::placeholder{color:#fff !important;opacity:.8}.sf-footer .mktoForm .mktoButtonWrap.mktoSimple .mktoButton{background-color:var(--ui-01) !important;color:#fff !important;width:100% !important;padding:12px 16px !important;border:1px solid var(--ui-01) !important;background-image:none !important;border-radius:48px;text-transform:uppercase;font-weight:800 !important;font-family:'Texta',sans-serif !important;font-size:16px !important;line-height:1.2}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoHtmlText\u003Espan,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap .mktoLabel\u003Espan,.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap label.mktoLabel{color:#fff !important}.sf-footer__newsletter-title p:not(:first-child){margin-top:8px !important}.sf-footer__newsletter-title p b{font-weight:800 !important;font-family:'Texta',sans-serif !important;font-size:22px !important;line-height:1.2}.sf-footer__newsletter-title p:last-child{font-size:14px !important;opacity:.8}.sf-footer__link-group li a[target=\"_blank\"]::after{content:'';display:inline-block;width:10px;height:10px;margin-left:5px;background-image:url(\"data:image/svg+xml,%3Csvg width='11' height='11' viewBox='0 0 11 11' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M6.72222 1.22222C6.38471 1.22222 6.11111 .948616 6.11111 .611111C6.11111 .273607 6.38471 0 6.72222 0H10.3889C10.551 0 10.7064 .0643867 10.821 .178988C10.9356 .293596 11 .449032 11 .611111V4.27778C11 4.61529 10.7264 4.88889 10.3889 4.88889C10.0514 4.88889 9.77778 4.61529 9.77778 4.27778V2.08647L4.09879 7.76545C3.86013 8.00409 3.4732 8.00409 3.23454 7.76545C2.99589 7.52681 2.99589 7.13986 3.23454 6.90122L8.91355 1.22222H6.72222ZM0 2.44444C0 1.76943 .547207 1.22222 1.22222 1.22222H4.27778C4.61529 1.22222 4.88889 1.49583 4.88889 1.83333C4.88889 2.17084 4.61529 2.44444 4.27778 2.44444H1.22222V9.77778H8.55556V6.72222C8.55556 6.38471 8.82915 6.11111 9.16667 6.11111C9.50418 6.11111 9.77778 6.38471 9.77778 6.72222V9.77778C9.77778 10.4528 9.23059 11 8.55556 11H1.22222C.547207 11 0 10.4528 0 9.77778V2.44444Z' fill='white'/%3E%3C/svg%3E%0A\");background-size:contain;background-repeat:no-repeat;background-position:center}.sf-footer__link-group ul,.sf-footer__link-group li{margin:0;padding:0;list-style-type:none}.sf-footer__link-group ul{margin-top:20px !important}.sf-footer__link-group li{margin-top:15px}.sf-footer div.sf-footer__link-group\u003Espan\u003Ep\u003Ea,.sf-footer div.sf-footer__link-group\u003Espan\u003Ep{color:var(--ui-01) !important;font-weight:800 !important;font-family:'Texta',sans-serif !important;font-size:20px !important;line-height:1.2}.sf-footer__link-group li a{opacity:.9;color:#fff !important;font-weight:500 !important;font-size:15px !important;line-height:1.3}.sf-footer__link-group li a:hover{opacity:1}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container::before,.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container::after{display:none}.sf-footer__column{flex-grow:1}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:not(:first-child){width:50%}@media (min-width:800px){.sf-footer__legal-links ul{justify-content:flex-start;text-align:left}.sf-footer__social{justify-content:flex-end}.sf-footer__legal-links ul{padding-left:24px}.sf-footer__legal-container\u003E.container\u003E.cmp-container\u003E.aem-container{text-align:right;flex-wrap:nowrap}.sf-footer__legal-links.align-left ul{justify-content:flex-start}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;justify-content:space-between;flex-direction:row}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:auto !important;max-width:200px}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{flex-grow:1;order:2;width:100% !important;max-width:none}.sf-footer__legal-container\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:auto}}@media screen and (min-width:1380px){.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container{flex-wrap:nowrap}.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{padding-right:48px;max-width:380px;background-color:rgba(3,24,35,.4);padding:32px;margin-left:48px;border-radius:16px}.sf-footer__link-group li,.sf-footer__link-group li a{font-size:14px !important;line-height:1.3}}@media screen and (max-width:991px){.sf-footer-grid__inner\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv:first-child{order:2;margin-top:24px !important}}@media screen and (max-width:420px){.is-reduced-mobile .heading-1-v2,.is-reduced-mobile .heading-1-v2-sm{font-size:32px;line-height:28px}}.quote-content-chip{background-color:var(--ui-background-05);padding:24px;border-radius:12px;position:relative}.quote-content-chip .black-blue-text-color .snowflake-title-v2-line\u003Espan{color:rgba(0,0,0,.8) !important;font-size:15px !important;line-height:1.5 !important;font-family:'Lato',sans-serif;font-weight:400 !important}.quote-content-chip .black-blue-text-color .snowflake-title-v2-line\u003Espan:not(:first-child){max-width:calc(100% - 200px)}.quote-content-chip .black-blue-text-color .snowflake-title-v2-line\u003Espan:nth-child(2){font-family:'Texta',sans-serif;color:#000 !important;font-size:20px !important;font-weight:800 !important;margin-top:24px}.quote-content-chip .snowflake-content-chip-image{width:140px !important}@media screen and (min-width:992px){.quote-content-chip .snowflake-content-chip-image{position:absolute !important;bottom:24px;right:16px}}@media screen and (max-width:991px){.quote-content-chip .snowflake-content-chip-image{margin-bottom:40px}.quote-content-chip{flex-direction:column}}#spa-root{background-color:#fff}.lowercase .snowflake-title-v2-line{text-transform:none !important}.centered .snowflake-logo-content-container-inner{justify-content:center}div.snowflake-linklist-dropdown-menu{max-height:380px}.first-line-blue .snowflake-typographyv2 .snowflake-title-v2-line:first-child{color:var(--ui-01) !important}.is-front{position:relative;z-index:2}.use-case-body .snowflake-text h1,.use-case-body .snowflake-text h2,.use-case-body .snowflake-text h3,.use-case-body .snowflake-text h4,.use-case-body .snowflake-text h5,.use-case-body .snowflake-text h6{font-family:'Texta',sans-serif;color:#000;margin:.25rem 0 0 0}.pc-hero .button-group\u003E.container\u003E.cmp-container\u003E.aem-container{justify-content:flex-start}.sf-footer .mktoFormRow .mktoHtmlText span{font-family:'Lato',sans-serif !important}.snowflake-button-primary.snowflake-button-blue .snowflake-button-container{justify-content:center}.related-chip-25{background-color:#fff;border:1px solid rgba(204,204,204,.5);border-radius:8px;padding:20px;position:relative}.related-chip-25:hover{box-shadow:rgba(152,162,179,.1) 0 10px 20px 0}.related-chip-25:hover::after{right:24px;transition:300ms ease right}.related-chip-25::after{content:'';display:block;transition:300ms ease right;background-image:url(\"data:image/svg+xml,%3Csvg width='8' height='14' viewBox='0 0 8 14' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7.66699 7C7.66699 6.6571 7.53559 6.32825 7.30169 6.08578L2.34446 .947072C1.84529 .429617 1.0164 .429617 .517219 .947072C.0427878 1.43887 .042788 2.21798 .517219 2.70978L4.65591 7L.51722 11.2902C.0427889 11.782 .0427887 12.5611 .51722 13.0529C1.0164 13.5704 1.84529 13.5704 2.34447 13.0529L7.30169 7.91421C7.53559 7.67175 7.66699 7.34289 7.66699 7Z' fill='%2329B5E8'/%3E%3C/svg%3E%0A\");width:8px;height:14px;display:block;position:absolute;right:30px;top:50%;transform:translateY(-50%);background-size:contain;background-position:center;background-repeat:no-repeat}.related-chip-25 .heading-5-v2{font-size:22px;line-height:1.1}.related-chip-25 .snowflake-content-chip-image{width:48px;flex-shrink:0}.related-chip-25 .snowflake-content-chip-image__image{aspect-ratio:1;height:auto;object-fit:contain}.related-chip-25 .snowflake-content-chip-button{display:none}.related-chip-25 .snowflake-content-chip-content-without-tag{flex-grow:1;padding-right:24px}.case-study-25.small-logo .snowflake-case-study-card-logo img{width:60px !important}.swiper-slide .case-study-25{width:95%;margin-left:auto;margin-right:auto}.case-study-25 .snowflake-case-study-card-logo img{width:140px !important;height:auto !important;transform:none !important;margin:24px 0 8px 0}.case-study-25 .snowflake-case-study-card-image__image{object-position:left center}.case-study-25 .snowflake-case-study-card-information-container{padding-right:24px}.case-study-25 ul{list-style-type:none;padding:0;margin:8px 0 0 0}.case-study-25 li{font-size:15px !important;line-height:1.3 !important;display:flex;flex-direction:column;border-left:4px solid var(--ui-01);padding-left:24px;margin-top:24px;color:#535862;gap:4px}.case-study-25 li b{display:block;font-family:'Texta',sans-serif;font-weight:900 !important;font-size:48px !important;line-height:.9 !important;color:var(--ui-01)}.case-study-25 .snowflake-case-study-card-description p{color:#535862}.case-study-25 .snowflake-case-study-card-description p:nth-child(2):not(:has(a)){color:#000;font-family:Texta;font-size:30px !important;line-height:1 !important;font-style:normal;font-weight:700;text-indent:-8px}.case-study-25.is-story .snowflake-case-study-card-description p:nth-child(2):not(:has(a)){text-indent:0}.case-study-25 .snowflake-case-study-card-key-card{background-color:transparent}.case-study-25 .snowflake-case-study-card-button{display:none}.case-study-25{border-radius:24px;overflow:hidden}@media screen and (min-width:1024px){.case-study-25 .snowflake-case-study-card-left-container{position:static;width:60%;min-height:0}.case-study-25 .snowflake-case-study-card-right-container::after{content:'';display:block;width:60%;max-width:340px;padding-bottom:50%;background-image:url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' fill='none' viewBox='0 0 22 16' class='snowflake-pushdown-banner-placeholder-arrow'%3E%3Cpath fill='%2329B5E8' fill-rule='evenodd' d='M17.865 8.756c.088-.274.124-.555.118-.834a2.551 2.551 0 0 0-1.3-2.142L7.887.76C6.645.055 5.063.475 4.35 1.7a2.535 2.535 0 0 0 .947 3.494l4.916 2.809-4.916 2.801a2.543 2.543 0 0 0-.947 3.502c.713 1.222 2.295 1.64 3.537.934l8.796-5.024a2.541 2.541 0 0 0 1.182-1.46Z' clip-rule='evenodd'%3E%3C/path%3E%3C/svg%3E\");background-size:contain;background-repeat:no-repeat;position:absolute;top:-10%;left:-20%}.case-study-25 .snowflake-case-study-card-right-container{max-width:none;width:40%;position:absolute;top:-5%;right:-5%;z-index:0;height:110%}}@media screen and (min-width:768px){.case-study-25 li{max-width:50%}.case-study-25 ul{display:flex;gap:48px}}.snowflake-text.section-eyebrow p{margin-left:auto;margin-right:auto;margin-bottom:16px !important}.snowflake-text.section-eyebrow p,.snowflake-text.eyebrow-text p{text-transform:uppercase;font-family:'Texta',sans-serif !important;font-weight:800 !important;letter-spacing:.025em;margin-bottom:12px;line-height:1.1 !important}.snowflake-title-v2.dynamic .heading-2-v2 span.snowflake-title-v2-line{font-size:clamp(2.5rem,4.5vw,4rem) !important;line-height:.82 !important}.checklist ul{padding:0;margin:0}.checklist ul li{list-style-type:none;padding-left:32px;position:relative}.checklist ul li:not(:last-child){margin-bottom:1em}.checklist ul li::before{content:'';display:inline-block;width:20px;height:20px;background-image:url(\"data:image/svg+xml,%3Csvg width='24' height='25' viewBox='0 0 24 25' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Crect y='.985352' width='24' height='24' rx='12' fill='%23D4F0FA'/%3E%3Cpath d='M7.28613 13.2967L10.7147 16.7253L17.5718 9.86816' stroke='%2329B5E8' stroke-width='2' stroke-linecap='round' stroke-linejoin='round'/%3E%3C/svg%3E%0A\");background-size:contain;background-repeat:no-repeat;position:absolute;top:3px;left:0}.last-line-blue .snowflake-typographyv2 .snowflake-title-v2-line:last-child{color:var(--ui-01)}.snowflake-text p sup{line-height:0}.snowflake-title-v2.lowercase .heading-3-v2{font-size:28px;line-height:1;text-transform:none;font-weight:700}.snowflake-title-v2.lowercase .heading-2-v2{font-size:32px;line-height:1;text-transform:none;font-weight:700}.content-chip-new{border:1px solid rgba(204,204,204,.5);border-radius:16px;overflow:hidden}.content-chip-new .snowflake-image-container{border-radius:0;display:none}.content-chip-new .snowflake-content-chip-image{margin-right:0;max-width:180px;flex-shrink:0}.content-chip-new .snowflake-content-chip-content{padding:24px}.content-chip-new .black-blue-text-color .snowflake-title-v2-line:first-child{font-size:24px;line-height:1.1}.content-chip-new .black-blue-text-color .snowflake-title-v2-line:not(:first-child){font-family:'Lato',sans-serif;font-size:17px;color:#535862 !important;font-weight:500;line-height:1.45;margin-top:8px;display:none}div.snowflake-text a{font-weight:normal;color:var(--ui-01);text-decoration:underline;text-underline-offset:4px;text-decoration-style:dotted !important;text-decoration-color:transparent;transition:300ms ease text-decoration-color}div.snowflake-text a:hover{text-decoration-color:var(--ui-01);transition:300ms ease text-decoration-color}.footer-nav__link-group .snowflake-button-container,.subnav__item--button,.snowflake-card-v2-advanced-button .snowflake-button-container{justify-content:flex-start}.button-container\u003E.container\u003E.cmp-container\u003E.aem-container{align-items:center}.button-container\u003E.container\u003E.cmp-container\u003E.aem-container .snowflake-button-primary+.snowflake-button-link{margin-left:12px !important}.snowflake-button-regular.snowflake-button-link .snowflake-button-container{font-size:18px !important;text-align:left;justify-content:flex-start;line-height:1.4 !important}body .snowflake-card-v2-advanced{border:1px solid rgba(204,204,204,.5);border-radius:var(--spacing-02);transition:300ms ease all}body .snowflake-card-v2-advanced:hover{transform:translateY(-10px);box-shadow:rgba(152,162,179,.1) 0 10px 20px 0;transition:300ms ease all}body .snowflake-card-v2-advanced-inner{border-bottom:none}body .snowflake-card-v2-advanced-image{line-height:0}body .snowflake-card-v2-advanced-image__image{aspect-ratio:16 / 9}body .snowflake-card-v2-advanced-content{position:relative}body .snowflake-card-v2-advanced-content::after{content:'';display:block;position:absolute;bottom:0;left:0;transition:300ms ease all;width:20%;height:4px;background-color:var(--ui-01);opacity:0}body .snowflake-card-v2-advanced:hover .snowflake-card-v2-advanced-content::after{width:100%;opacity:1;transition:300ms ease all}body .snowflake-card-v2-advanced .snowflake-button-link.snowflake-button-blue .snowflake-button-container\u003E.link-icon{transition:300ms ease transform}body .snowflake-card-v2-advanced:hover .snowflake-button-link.snowflake-button-blue .snowflake-button-container\u003E.link-icon{transform:translateX(4px);transition:300ms ease transform}.six-columns\u003E.container\u003E.cmp-container\u003E.aem-container,.three-columns\u003E.container\u003E.cmp-container\u003E.aem-container,.four-columns\u003E.container\u003E.cmp-container\u003E.aem-container,.five-columns\u003E.container\u003E.cmp-container\u003E.aem-container{display:flex;flex-wrap:wrap;gap:24px}.six-columns.align-center\u003E.container\u003E.cmp-container\u003E.aem-container,.three-columns.align-center\u003E.container\u003E.cmp-container\u003E.aem-container,.four-columns.align-center\u003E.container\u003E.cmp-container\u003E.aem-container,.five-columns.align-center\u003E.container\u003E.cmp-container\u003E.aem-container{justify-content:center}.three-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:100%;margin:0 !important}.six-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv,.four-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv,.five-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(50% - 12px);margin:0 !important}@media screen and (min-width:768px){.three-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(50% - 12px)}.six-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv,.four-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv,.five-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(33.333% - 16px)}}@media screen and (min-width:1024px){.snowflake-title-v2.lowercase .heading-3-v2{font-size:34px}.snowflake-title-v2.lowercase.larger .heading-2-v2{font-size:44px;line-height:.95}.three-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(33.333% - 16px)}.four-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(25% - 18px)}.five-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(20% - 19.2px)}.six-columns\u003E.container\u003E.cmp-container\u003E.aem-container\u003Ediv{width:calc(16.6666% - 20px)}.snowflake-title-v2.lowercase .heading-3-v2{font-size:28px !important}}@media screen and (min-width:1200px){.snowflake-title-v2.lowercase .heading-2-v2{font-size:40px}.content-chip-new .snowflake-content-chip-content{padding:32px}.content-chip-new .snowflake-image-container,.content-chip-new .black-blue-text-color .snowflake-title-v2-line:not(:first-child){display:block}}.promo-banner-25{border-radius:16px;overflow:hidden}.promo-banner-25 .snowflake-premium-content-banner-image-container{position:relative;max-width:380px}.promo-banner-25 .snowflake-text{color:#535862}.promo-banner-25 .snowflake-premium-content-banner-image__image{transform:translateY(8px);transition:300ms ease transform;border-radius:0;width:85%;margin:0 auto;display:block;position:relative;z-index:1}.promo-banner-25 .snowflake-premium-content-banner-image__link:hover .snowflake-premium-content-banner-image__image{transform:translateY(0);transition:300ms ease transform}.promo-banner-25 .snowflake-premium-content-banner-image__inner{height:auto;padding-top:24px}.promo-banner-25 .snowflake-premium-content-banner-image__link{position:relative;z-index:1;height:auto}.promo-banner-25 .snowflake-premium-content-banner-image__link::after{content:'';display:block;position:absolute;clip-path:polygon(0 0,66% 0,100% 100%,0 100%);bottom:0;left:0;width:100%;height:100%;background:var(--ui-01);transition:300ms ease width}.promo-banner-25 .snowflake-premium-content-banner-image__link:hover::after{width:110%;transition:300ms ease width}.sf-footer .snowflake-marketo-form .mktoFormRow .mktoFieldWrap select{background-position:95% 50%}.sf-footer__disclaimers .text-size-small .snowflake-text p{color:#fff !important;font-size:10px !important;opacity:.8}@media screen and (min-width:768px){.sf-footer__disclaimers .text-size-small .snowflake-text p{font-size:12px !important}}@media screen and (max-width:1023px){.mobile-top-padding{padding-top:64px}}@media (max-width:799px){.sf-footer .snowflake-marketo-form .mktoButtonWrap.mktoNative .mktoButton{width:100% !important}.sf-footer__logo{text-align:center;display:block;margin:0 auto}}.customer-card .snowflake-card-v2-advanced-image{aspect-ratio:4.35 / 1}.customer-card .snowflake-card-v2-advanced-image__image{width:100%;height:100%;padding-left:8px;object-fit:contain;object-position:left center;margin:0 !important;aspect-ratio:initial}.customer-card .snowflake-card-v2-advanced-image__inner{height:110px}.customer-card .snowflake-card-v2-advanced-tag-indicator{display:none}.pc-hero .snowflake-container-arrow-small-gray-image{top:-34% !important;width:18% !important}.pc-hero .snowflake-container-arrow-small-gray-image path{fill:var(--ui-01);opacity:1}@media screen and (max-width:767px){.mobile-padding-top{padding-top:64px}.hide-mobile{display:none !important}.pc-hero{padding-top:52px}.pc-hero .snowflake-text p,.pc-hero .left-alignment .snowflake-title-v2-line,.pc-hero h1 span{text-align:center !important}}div.snowflake-pushdown-banner-button{margin-top:0}.button-group.align-center\u003E.container\u003E.cmp-container\u003E.aem-container{align-items:center;justify-content:center !important}.text-center .snowflake-breadcrumb-swiper .swiper-wrapper{justify-content:center}div.snowflake-breadcrumb a.snowflake-breadcrumb-item,.snowflake-breadcrumb div.snowflake-breadcrumb-item{text-transform:none;font-weight:500}.snowflake-breadcrumb svg{display:none !important}.snowflake-breadcrumb a:has(svg)::after{content:'/';margin:0 12px;color:#666}.hide-filters .snowflake-filterable-and-searchable-grid-top-part{display:none !important}.page-section{padding-left:24px;padding-right:24px}@media screen and (min-width:768px){.page-section{padding-left:48px;padding-right:48px}}.download-card pre[class*=language-]{overflow-x:scroll !important}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"}},":itemsOrder":["container_copy","container_573483281_","markup_editor_copy"],":type":"snowflake-site/components/container"}},":itemsOrder":["root"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"markup_editor":{"id":"markup-editor-09859f7e77","title":"Quickstarts Overrides","cssContent":".snowflake-markdown blockquote{padding:24px 32px;background:#f6f9fa;border:1px solid #29b5e8;border-radius:16px}.snowflake-markdown .snowflake-image-container img{width:auto !important;max-width:100%}.snowflake-markdown .snowflake-text ol{padding-left:20px !important}.snowflake-markdown .snowflake-text li{margin:0 0 12px 0 !important}.snowflake-markdown h3.snowflake-markdown-h3{font-size:20px !important;font-family:Texta,sans-serif !important}@media (min-width:768px){.snowflake-markdown h3.snowflake-markdown-h3{font-size:28px !important}}","isGSAPEnabled":false,":type":"snowflake-site/components/markup-editor"}},":itemsOrder":["experiencefragment-banner","experiencefragment-header","markup_editor_1950346551","responsivegrid","modal_container","experiencefragment-footer","markup_editor"],":type":"wcm/foundation/components/responsivegrid"}},":itemsOrder":["root"],":hierarchyType":"page",":path":"/content/snowflake-site/global/en/developers/guides/data-engineering-with-notebooks",":type":"snowflake-site/components/structure/page","isPasswordProtected":false,"analyticsContentTags":["snowflake-site:taxonomy/solution-center/certification/quickstart","snowflake-site:taxonomy/solution-center/certification/community-sourced","snowflake-site:taxonomy/solution-center/includes/architecture","snowflake-site:taxonomy/product/data-engineering"],"analyticsEnabled":true,"coveoConfig":{"pipeline":"snowflake.com","apiKey":"xx335921a6-2a0a-40f2-a167-e390b4766c3d","organizationId":"snowflakecomputingproduction8neljofn","searchHub":"snowflake.com"},":mappedPath":"/en/developers/guides/data-engineering-with-notebooks/","locale":"en"}