{"templateName":"fundamentals-template","allowedRenditionsWidth":["320","480","640","768","960","1200","1440","1920"],"cssClassNames":"fundamentals-page page basicpage summit-page","canonicalLink":"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/automl/","robotsTags":["index","follow"],"language":"ja","description":"AutoML（自動機械学習）とは、前処理からアルゴリズム選定、ハイパーパラメータ調整までを自動化する技術です。本ガイドでは、仕組みと主要コンポーネント、需要予測や不正検知などの6つのユースケース、導入時の制約と選定の考え方まで解説します。","title":"AutoMLとは：仕組みと活用事例、自動化の限界｜Snowflake","analyticsPageType":"homepage","analyticsCategory":"general","analyticsSubCategory":"","excludeFromAnalytics":false,"isPasswordProtected":false,"analyticsContentTags":["snowflake-site:taxonomy/content-type/fundamentals","snowflake-site:taxonomy/product/ai"],"analyticsEnabled":true,":hierarchyType":"page",":path":"/content/snowflake-site/global/ja/artificial-intelligence/machine-learning/automl",":items":{"root":{"columnCount":12,"columnClassNames":{"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 aem-GridColumn--offset--default--0 aem-GridColumn--default--none","experiencefragment":"aem-GridColumn aem-GridColumn--default--12 aem-GridColumn--offset--default--0 aem-GridColumn--default--none","markup_editor":"aem-GridColumn aem-GridColumn--default--12","modal_container":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12",":items":{"experiencefragment-banner":{"id":"experiencefragment-1d054369ac","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/ja/site/pushdown-banner/master/jcr:content","configured":true,":items":{"root":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"pushdown_banner_copy":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-2614eb1297",":items":{"pushdown_banner_copy":{"id":"pushdown-banner-b3ac21e412","contentHeadline":"Snowflake World Tour Tokyo","contentDescription":"オンデマンド配信を開始しました。あの知的興奮を振り返る期間限定のチャンスをお見逃しなく。","contentJustifyContent":"center","linkStyle":"text-white","linkCTA":{"id":"link-cta","heapButtonClasses":["pushdown_banner"],"showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/ja/world-tour/tokyo/?utm_cta=homepage-pushdown-banner"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"視聴登録はこちら"},":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-2e378ea770","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/ja/site/mega-nav-header/master/jcr:content","configured":true,":items":{"root":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"mega_header":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-969216a6f0",":items":{"markup_editor":{"id":"markup-editor-5e275c560c","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:'Snowflakeで実現できること\u003E';display:block;color:var(--ui-01);margin-top:16px}.nav-item__platform-parent .snowflake-mega-nav-nav-item-description::after{content:'プラットフォームを見る\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}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"mega_header":{"additionalClasses":"heap-nav-header","layout":"SIMPLE","id":"container-69173e6913","appliedCssClassNames":"snowflake-header-container white",":items":{"nav_mega":{"activeItem":"item_1719963657751_c_663444255","id":"tabs-00fd50bbac",":type":"snowflake-site/components/nav/nav-mega",":items":{"item_1719963657751_c_663444255":{"id":"nav-dropdown-menu-3c7f344663","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-31a3d17b87",":items":{"nav_column":{"additionalClasses":"nav-platform-sidebar","numberOfSubColumns":"one-column","minWidth":"230","maxWidth":"350","layout":"SIMPLE","id":"container-1d2c86bf5f",":items":{"nav_item_copy_copy_2_793631646":{"id":"nav-item-cc4da86cbb","additionalClasses":"nav-item__platform-parent","linkDescription":"データの種類や規模に関係なくビジネスをセキュアに接続するフルマネージドのプラットフォームで、AIプロダクトやアプリなどを開発できます。","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/platform/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflakeプラットフォーム"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-e4953e5f72","additionalClasses":"nav-item nav-item--si","linkDescription":"あらゆる知識を集約、信頼のエンタープライズAIエージェントが応える","flag":"NOW GA","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/snowflake-cowork/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflake CoWork"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2_836345186":{"id":"nav-item-0f62c309d9","additionalClasses":"blue-icon","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/analytics/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"アナリティクス"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2":{"id":"nav-item-b1fc2132a6","additionalClasses":"blue-icon","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/ai/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"AI"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy_2_1314771042":{"id":"nav-item-2f5560e279","additionalClasses":"blue-icon","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/data-engineering/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"データエンジニアリング"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634_929542939":{"id":"nav-item-391da24909","additionalClasses":"blue-icon","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/applications-and-collaboration/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"アプリケーションとコラボレーション"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634_115249434":{"id":"nav-item-77aa260e40","additionalClasses":"blue-icon","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/transactions/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"トランザクション"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-9ef45810a0",":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_copy_2_793631646","nav_item_copy","nav_item_copy_copy_2_836345186","nav_item_copy_copy_2","nav_item_copy_copy_2_1314771042","nav_item_copy_144634_929542939","nav_item_copy_144634_115249434","nav_item"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy_copy":{"additionalClasses":"meganav-platform-features","navColumnTitle":"注目の機能","numberOfSubColumns":"two-columns","layout":"SIMPLE","id":"container-4484013ab3",":items":{"nav_item_copy_212715_1193254885":{"id":"nav-item-bd86a0f197","linkDescription":"SnowflakeネイティブAIコーディングエージェント","flag":"New","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/snowflake-coco/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflake CoCo"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_898460603":{"id":"nav-item-6a7e16d9c9","linkDescription":"Snowflake上で動作する、完全な互換性を備えたオープンソースのPostgres","flag":"NOW GA","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/postgres/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Postgres"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_716480505":{"id":"nav-item-2e4595c794","propertiesId":"testID","linkDescription":"業界をリードするLLMへのほぼ即時のアクセス","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/cortex/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Cortex AI"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_212715":{"id":"nav-item-762f9ccd00","linkDescription":"統合のためのスムーズなデータ移動","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/openflow/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Openflow"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_655386423":{"id":"nav-item-503ee93cb8","propertiesId":"testID","linkDescription":"数分で接続可能なサードパーティデータソース","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/marketplace/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"マーケットプレイス"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590_718021728":{"id":"nav-item-1bc1fcd109","linkDescription":"データチームやAIチームのためのインタラクティブな開発環境","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/notebooks/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Notebook"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590_622392430":{"id":"nav-item-bcdce01c83","linkDescription":"Pythonやその他の言語を実行するためのライブラリとコード実行環境","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/snowpark/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowpark"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_185565":{"id":"nav-item-946284b628","linkDescription":"プライバシーを保護したデータコラボレーション","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/data-clean-rooms/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"データクリーンルーム"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590_983061516":{"id":"nav-item-8c5b545e39","linkDescription":"Pythonスクリプトをウェブアプリに変換するためのフレームワーク","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/streamlit-in-snowflake/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Streamlit（英語）"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_258535199_c":{"id":"nav-item-17de5f4d7a","propertiesId":"workload-nav-1","linkDescription":"Snowflakeネイティブなアプリのエンドツーエンドでの作成と配布","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/native-apps/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ネイティブアプリ"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_212715_1193254885","nav_item_898460603","nav_item_copy_716480505","nav_item_copy_212715","nav_item_copy_655386423","nav_item_copy_660590_718021728","nav_item_copy_660590_622392430","nav_item_copy_185565","nav_item_copy_660590_983061516","nav_item_258535199_c"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_676020780":{"numberOfSubColumns":"one-column","maxWidth":"300","layout":"SIMPLE","id":"container-9e517f9f2c",":items":{"nav_item_copy_copy":{"id":"nav-item-fa9b07edc2","additionalClasses":"is-light-gray-icon","linkDescription":"ユニバーサルAIカタログ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/horizon/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Horizonカタログ"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_660590":{"id":"nav-item-47dd9e514a","linkDescription":"一元化されたUIによる合理化されたモデル開発とMLOps","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/product/features/end-to-end-ml-workflows/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflake ML"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_41538387_co":{"id":"nav-item-75b0fb2df3","linkDescription":"Snowflakeでトランザクションワークロードと分析ワークロードを統合し、さらなる簡素化を実現","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/product/features/unistore/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ユニストア（英語）"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_copy","nav_item_copy_660590","nav_item_41538387_co"],":type":"snowflake-site/components/nav/nav-column"}},":itemsOrder":["nav_column","nav_column_copy_copy","nav_column_676020780"],":type":"snowflake-site/components/nav/nav-column/nav-column-container"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"プロダクト"},"nav_dropdown_menu_2":{"id":"nav-dropdown-menu-517f9ddb61","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-532876e1c2",":items":{"nav_column":{"navColumnTitle":"業界","numberOfSubColumns":"one-column","minWidth":"280","layout":"SIMPLE","id":"container-3ed1b97518","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"nav_item_copy_153342":{"id":"nav-item-0ece9255c6","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/manufacturing/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"製造"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1533429516":{"id":"nav-item-a906111143","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/manufacturing/automotive/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"自動車"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-accc9a23d4","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/financial-services/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"金融サービス"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1149488919":{"id":"nav-item-8a60d8d2ac","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/retail-consumer-goods/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"小売・消費財"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_361384674":{"id":"nav-item-b844ef046d","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/telecom/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"通信"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-d9860bd930","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/advertising-media-entertainment/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"広告・メディア・エンターテイメント"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-39f683c63d","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/healthcare-and-life-sciences/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ヘルスケア・ライフサイエンス"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_361384_311786134":{"id":"nav-item-dac85a66a2","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/travel-hospitality/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"旅行・ホスピタリティ"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_361384":{"id":"nav-item-024041c467","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/manufacturing/energy/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"エネルギー"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144445":{"id":"nav-item-c58bf4e050","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/public-sector/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"官公庁・公的機関"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1444458226":{"id":"nav-item-69fa6053b2","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/industries/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"すべての業種"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item_copy_153342","nav_item_copy_1533429516","nav_item_copy","nav_item_copy_1149488919","nav_item_copy_361384674","nav_item","nav_item_copy_1970515619","nav_item_copy_361384_311786134","nav_item_copy_361384","nav_item_copy_144445","nav_item_copy_1444458226"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_copy":{"navColumnTitle":"部門","numberOfSubColumns":"one-column","minWidth":"160","layout":"SIMPLE","id":"container-770f5546cf",":items":{"nav_item":{"id":"nav-item-cbff492015","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/departments/finance/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"財務"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-8f019f83cd","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/departments/information-technology/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"IT"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-47e8797ec6","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/departments/marketing/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"マーケティング"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1533429516":{"id":"nav-item-14ad2cfa26","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/solutions/departments/cybersecurity/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"サイバーセキュリティ"},":type":"snowflake-site/components/nav/nav-item"}},":itemsOrder":["nav_item","nav_item_copy","nav_item_copy_1970515619","nav_item_copy_1533429516"],":type":"snowflake-site/components/nav/nav-column"},"nav_column_833417450":{"navColumnTitle":"イネーブルメントソリューション","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-5cf049583a",":items":{"nav_item_copy_107772":{"id":"nav-item-7b2a87f7ce","linkDescription":"統合プラットフォームへの移行の不安を解消","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/migrate-to-the-cloud/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"AIデータクラウドへの移行"},"icon":{"id":"icon","height":"64","alt":"Cloud icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779170239130/nav-icon-cloud.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy":{"id":"nav-item-b44b0e6165","linkDescription":"Snowflakeのエキスパートがビジネスの加速と目標達成を支援","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/solutions/services-delivery/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"サービス提供（英語）"},"icon":{"id":"icon","height":"64","alt":"Migrate icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779170420240/nav-icon--migrate.svg","width":"64",":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":"パートナーソリューション","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-cb13706221",":items":{"nav_item":{"id":"nav-item-68742bb122","linkDescription":"製品、ソリューション、クラウドのパートナープログラム","button":{"id":"button","showOutboundIcon":false,"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflakeパートナーネットワーク"},"icon":{"id":"icon","height":"64","alt":"Partner Network icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779170253125/nav-icon--partner-network.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-bdc9b42674","linkDescription":"展開強化のためのパートナー、アプリ、ソリューション","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/partners/all-partners/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"パートナーを見つける（英語）"},"icon":{"id":"icon","height":"64","alt":"Partner Finder icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1764979537932/nav-icon--partner-finder.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1970515619":{"id":"nav-item-aff8102185","linkDescription":"ライブイベントやバーチャルイベントの開催","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/why-snowflake/partners/event-partnership-opportunities/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"パートナーのためのイベント（英語）"},"icon":{"id":"icon","height":"64","alt":"Calendar icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740635895261/nav-icon--events.svg","width":"64",":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":"ソリューション"},"item_1719963657751_c":{"id":"nav-dropdown-menu-b342855c31","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-e9e0a04154",":items":{"nav_column":{"numberOfSubColumns":"one-column","minWidth":"230","maxWidth":"350","layout":"SIMPLE","id":"container-cc532dec53",":items":{"nav_item_copy_copy_2_793631646":{"id":"nav-item-66dae3547f","additionalClasses":"nav-item__platform-parent-why-sf","linkDescription":"ローカルまたはグローバルなコラボレーションにより、新たなインサイトの発見やこれまで認識できなかったビジネス機会の創出が可能になり、シームレスな体験の実現を通じて顧客理解が深まります。","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/why-snowflake/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Snowflakeを選ぶ理由"},":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","layout":"SIMPLE","id":"container-aeab93feeb",":items":{"nav_item":{"id":"nav-item-33acea5f31","propertiesId":"testID","linkDescription":"グローバルな組織によるSnowflakeの活用事例をケーススタディと動画で紹介","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/customers/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"カスタマーストーリー"},"icon":{"id":"icon","height":"64","alt":"Customer icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740635941203/nav-icon--partner-network.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_258535199":{"id":"nav-item-f14c239632","propertiesId":"workload-nav-1","linkDescription":"データやアプリの接続、共有、統合を可能にするAIデータクラウドの概要紹介","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/why-snowflake/what-is-data-cloud/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"AIデータクラウドとは"},"icon":{"id":"icon","height":"64","alt":"Cloud icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740635973565/nav-icon-cloud.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_185565":{"id":"nav-item-25084d810f","linkDescription":"組み込みの機能やクラウドインフラストラクチャの堅牢な保護などによる包括的なセキュリティ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/why-snowflake/snowflake-security-hub/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"セキュリティハブ"},"icon":{"id":"icon","height":"64","alt":"User with security lock icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779169641095/user-security-admins-ciso-icon.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-c89ff1c2d3","additionalClasses":"is-light-gray-icon","linkDescription":"TCOの最小化と継続的な価格性能比の最適化を通じて、経済的価値の最大化を実現","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/pricing-options/cost-and-performance-optimization/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"コストとパフォーマンスの最適化"},"icon":{"id":"icon","height":"64","alt":"Cost Optimization icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1764979571095/nav-icon-cost-optimization-performance.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_1860117577":{"id":"nav-item-42217d3272","linkDescription":"AIデータクラウドでアプリケーションを構築するスタートアップ企業","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/why-snowflake/startup-program/"},"accessibilityLabel":"Snowflake for Startups","linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"スタートアップ企業のためのSnowflake（英語）"},"icon":{"id":"icon","height":"64","alt":"Launch icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719963657751_c/nav_column_container/nav_column_copy_copy/nav_item_1860117577/icon.coreimg.svg/1779172755133/launch.svg","width":"65",":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_1860117577"],":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":"Snowflakeを選ぶ理由"},"item_1719961362824":{"id":"nav-dropdown-menu-6d1f37ca46","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-1f9c632920",":items":{"nav_column_copy":{"navColumnTitle":"つながる","numberOfSubColumns":"one-column","minWidth":"200","layout":"SIMPLE","id":"container-e535ceadac",":items":{"nav_item":{"id":"nav-item-fcf653d755","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/blog/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ブログ"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_180298689":{"id":"nav-item-f40de32143","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/events/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"イベント"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_1639361946":{"id":"nav-item-d508f8b4b3","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/support/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"サポート（英語）"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_680912746":{"id":"nav-item-ca22827453","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/contact/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"お問い合わせ"},":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":"学ぶ","numberOfSubColumns":"two-columns","layout":"SIMPLE","id":"container-c6c1e01524",":items":{"nav_item_copy":{"id":"nav-item-5fb54bb322","linkDescription":"eBook、ポッドキャスト、動画、ホワイトペーパー、その他","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/resources/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"リソースライブラリ"},"icon":{"id":"icon","height":"64","alt":"Notebooks icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779171979417/nav-icon--notebooks.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item":{"id":"nav-item-ada3922147","linkDescription":"Snowflakeの教育オファリングの概要","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/resources/learn/training/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"トレーニング（英語）"},"icon":{"id":"icon","height":"64","alt":"Training icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636044421/nav-icon--training.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_144634_1984107859":{"id":"nav-item-571b78ef9d","linkDescription":"エキスパートによる、さまざまな業界やユースケースについてのディスカッションとデモ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/webinars/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ウェビナー"},"icon":{"id":"icon","height":"64","alt":"Webinars icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1773154143134/nav-icon--webinars.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1438098918":{"id":"nav-item-07d5aa226e","linkDescription":"Snowflakeの技術業界プロフェッショナル認定資格","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/resources/learn/certifications/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"認定資格"},"icon":{"id":"icon","height":"64","alt":"Certification icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636064365/nav-icon--cert.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_143809":{"id":"nav-item-bfab17ed4a","linkDescription":"主要な機能を紹介する、毎週開催の製品デモとライブQ&A","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/live-demo/?lang=ja"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"ライブデモ"},"icon":{"id":"icon","height":"64","alt":"Live Demo icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636024013/nav-icon--live-demo.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_333890638":{"id":"nav-item-b57e2f618f","linkDescription":"習熟度に応じた、オンデマンドまたはインストラクターによるトレーニングコース","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://learn.snowflake.com/en/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Snowflake University（英語）"},"icon":{"id":"icon","height":"64","alt":"Education icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636071015/nav-icon--education.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_189945_905223977":{"id":"nav-item-e8acf0ffca","linkDescription":"Snowflakeの主要な機能を体験できる、インストラクターによるバーチャルワークショップ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/virtual-hands-on-lab/?lang=ja"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"ハンズオンラボ"},"icon":{"id":"icon","height":"64","alt":"Hands-on Labs icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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_905223977/icon.coreimg.svg/1740636037740/nav-icon--labs.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_189945":{"id":"nav-item-d11f70049c","linkDescription":"Snowflakeの研究者が執筆した学術論文","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/resources/publications/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Snowflake研究開発資料（英語）"},"icon":{"id":"icon","height":"64","alt":"Data Sheet","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779173639149/data-sheet.svg","width":"65",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_35712637":{"id":"nav-item-ad0271884d","linkDescription":"AIとデータに関する情報記事","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/fundamentals/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"AIデータクラウドの基礎"},"icon":{"id":"icon","height":"64","alt":"Fundamentals","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/site/mega-nav-header/master/_jcr_content/root/mega_header/nav_mega/item_1719961362824/nav_column_container/nav_column_44600420__826130542/nav_item_35712637/icon.coreimg.svg/1779172273319/nav-icon--notebooks.svg","width":"64",":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_905223977","nav_item_copy_189945","nav_item_35712637"],":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"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"リソースのご紹介"},"item_1719963657751":{"id":"nav-dropdown-menu-77f301e33a","enableDropdown":true,"nav_column_container":{"layout":"SIMPLE","id":"container-5f648907f8",":items":{"nav_column_copy_copy":{"navColumnTitle":"構築する","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-c4755efae2",":items":{"nav_item":{"id":"nav-item-a9968610cf","propertiesId":"testID","linkDescription":"構築とスケーリングに必要な開発リソースの概要","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"開発者のためのSnowflake（英語）"},"icon":{"id":"icon","height":"64","alt":"Developers icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1779172469867/nav-icon--devs.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1855651246":{"id":"nav-item-d5ffad2ea2","linkDescription":"リファレンスアーキテクチャ、ユースケース、ベストプラクティス","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/developers/guides/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"開発者ガイド"},"icon":{"id":"icon","height":"64","alt":"Solution Center icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1761757650759/nav-icon--solution-center.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-9b9a46c164","additionalClasses":"is-light-gray-icon","linkDescription":"最新のソフトウェアバージョン、ドライバー、ライブラリ、関連ドキュメント","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/downloads/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ダウンロード（英語）"},"icon":{"id":"icon","height":"28","alt":"Download icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636104927/nav-icon-download.svg","width":"28",":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":"学ぶ","numberOfSubColumns":"one-column","layout":"SIMPLE","id":"container-fb463b4797",":items":{"nav_item":{"id":"nav-item-bac37f8e90","propertiesId":"testID","linkDescription":"リファレンス、ガイド、チュートリアル、発表資料","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://docs.snowflake.com/ja"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"ドキュメント"},"icon":{"id":"icon","height":"64","alt":"Docs icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636111253/nav-icon--docs.svg","width":"64",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy":{"id":"nav-item-14a000aab0","additionalClasses":"is-light-gray-icon","linkDescription":"Snowflakeエンジニアが保守およびサポートしている重要プロジェクト","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/open-source/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"オープンソース（英語）"},"icon":{"id":"icon","height":"32","alt":"Open Source icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636127119/nav-icon-open-source.svg","width":"32",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_copy":{"id":"nav-item-9ad82d407c","additionalClasses":"is-light-gray-icon","linkDescription":"Snowflakeスキル向上のためのオンラインと対面のクラスやワークショップ","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/developers/northstar/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"ビルダー教育（英語）"},"icon":{"id":"icon","height":"32","alt":"Northstar logo","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636131947/nav-icon--northstar.svg","width":"32",":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-ced8e48b98",":items":{"nav_item":{"id":"nav-item-33453f0f88","propertiesId":"testID","linkDescription":"Snowflakeの技術リーダーによる機能のビルドについての情報","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/engineering-blog/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"エンジニアリングブログ（英語）"},"icon":{"id":"icon","height":"32","alt":"Developers icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636137545/nav-icon--developer-center.svg","width":"32",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/nav/nav-item"},"nav_item_copy_1855651246":{"id":"nav-item-479affd323","linkDescription":"Snowflake開発者とのヒント、コツ、ディスカッションの共有","button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://community.snowflake.com/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"コミュニティ（英語）"},"icon":{"id":"icon","height":"64","alt":"Partner Network icon","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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/1740636144841/nav-icon--partner-network.svg","width":"64",":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"},":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"開発者向け"},"item_1718247180324":{"id":"nav-dropdown-menu-a1e98a029b","enableDropdown":false,"link_url":"/ja/pricing-options/",":type":"snowflake-site/components/nav/nav-dropdown-menu","cq:panelTitle":"料金"}},":itemsOrder":["item_1719963657751_c_663444255","nav_dropdown_menu_2","item_1719963657751_c","item_1719961362824","item_1719963657751","item_1718247180324"]},"languagenavigation":{"id":"language-navigation-5666af8efe","languageNavItems":[{"title":"English","path":"/en/artificial-intelligence/machine-learning/automl/","locale":"en","active":false},{"title":"日本語","path":"/ja/artificial-intelligence/machine-learning/automl/","locale":"ja","active":true},{"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/artificial-intelligence/machine-learning/automl/","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":{"id":"button-03a65a05e3","heapButtonClasses":["contact_nav","heap-nav-contact"],"showOutboundIcon":true,"buttonLink":{"valid":true,"url":"/ja/contact-sales/"},"linkTargetContentType":"GENERIC","appliedCssClassNames":"snowflake-button-secondary snowflake-button-blue snowflake-button-compact",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"営業部門に問い合わせる"},"button_288358396":{"id":"button-ea1cb0e4bc","heapButtonClasses":["start_for_free_nav","heap-nav-start-for-free"],"showOutboundIcon":true,"buttonLink":{"valid":true,"url":"https://signup.snowflake.com/?_l=ja"},"linkTargetContentType":"GENERIC","appliedCssClassNames":"snowflake-button-primary snowflake-button-blue snowflake-button-compact",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"無料で開始"}},":itemsOrder":["nav_mega","languagenavigation","button","button_288358396"],":type":"snowflake-site/components/mega-header"}},":itemsOrder":["markup_editor","mega_header"],":type":"snowflake-site/components/container"}},":itemsOrder":["root"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"markup_editor":{"id":"markup-editor-c823ef5aaf","title":" ","jsContent":"window.addEventListener('click',(e)=\u003E{if(e.target.tagName==='LI'&&e.target.dataset.anchor){const target=document.getElementById(e.target.dataset.anchor);if(target){const targetPosition=target.getBoundingClientRect().top+window.pageYOffset-220;window.scrollTo({top:targetPosition,behavior:'smooth'});}}});","cssUrl":"/conf/snowflake-site/settings/wcm/templates/fundamentals-template/structure/_jcr_content/root/markup_editor.2632e417a335f89b.css",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false},"responsivegrid":{"columnCount":12,"columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","breadcrumb":"aem-GridColumn aem-GridColumn--default--12","hero_system":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12",":items":{"breadcrumb":{"id":"breadcrumb-d1d0a598e2","items":[{"id":"breadcrumb-d1d0a598e2-item-32c8cb0e6a","link":{"valid":true,"url":"/ja/artificial-intelligence/"},"active":false,"current":false,"title":"AI","appliedCssClassNames":"summit-page",":type":"snowflake-site/components/structure/page"},{"id":"breadcrumb-d1d0a598e2-item-fd5a1278e0","link":{"valid":true,"url":"/ja/artificial-intelligence/machine-learning/"},"active":false,"current":false,"title":"機械学習（ML）","appliedCssClassNames":"summit-page",":type":"snowflake-site/components/structure/page"},{"id":"breadcrumb-d1d0a598e2-item-c1d0029465","link":{"valid":true,"url":"/ja/artificial-intelligence/machine-learning/automl/"},"active":true,"current":true,"title":"AutoML","appliedCssClassNames":"summit-page",":type":"snowflake-site/components/structure/fundamentals-page"}],":type":"snowflake-site/components/breadcrumb"},"hero_system":{"id":"hero-system-ace8951cba","heroStyle":"tertiary","headline":{"id":"headline","type":"display2","lines":["AutoML（自動機械学習）とは：仕組みとユースケース、限界までを解説"],":type":"snowflake-site/components/title-v2"},"subheadline":{"id":"subheadline","text":"\u003Cp\u003EAutoML（自動機械学習）とは、データの前処理からアルゴリズムの選定、ハイパーパラメータの調整までを自動化する技術です。従来は数か月を要していた試行錯誤を数日規模へ短縮し、専門人材が不足する組織でもモデル構築を可能にします。本ガイドでは、仕組みと主要コンポーネント、代表的なユースケース、自動化しきれない領域までを解説します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},"position":"center",":type":"snowflake-site/components/hero-system","appliedCssClassNames":"snowflake-hero-system-background-grad-white"},"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-49bdfb5ed3","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","related_content":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-aa8e45d138","appliedCssClassNames":"snowflake-container snowflake-responsive-container-inner-padding-small",":items":{"flexible_column_cont":{"id":"flexible-column-container-18698a36ed","type":"2-column-25-75","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"medium","bottomPadding":"medium","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"propertiesCSSClasses":"use-case-body","backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-e2e5d845b1","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"text":{"id":"text-603dd18d7e","additionalClasses":"page-toc","text":"\u003Cul\u003E\r\n\u003Cli data-anchor=\"overview\"\u003E概要\u003C/li\u003E\r\n\u003Cli data-anchor=\"what\"\u003EAutoMLとは\u003C/li\u003E\r\n\u003Cli data-anchor=\"benefits\"\u003EAutoMLがモデル構築に革新をもたらす主な要因\u003C/li\u003E\r\n\u003Cli data-anchor=\"components\"\u003EAutoMLパイプラインを構成する主要コンポーネント\u003C/li\u003E\r\n\u003Cli data-anchor=\"use-cases\"\u003EAutoMLの代表的な6つのユースケース\u003C/li\u003E\r\n\u003Cli data-anchor=\"limitations\"\u003EAutoML導入における主な制限事項と課題\u003C/li\u003E\r\n\u003Cli data-anchor=\"conclusion\"\u003E結論\u003C/li\u003E\r\n\u003Cli data-anchor=\"faq\"\u003EAutoMLに関するよくある質問\u003C/li\u003E\r\n\u003Cli data-anchor=\"customer\"\u003ESnowflakeの機械学習をご利用のお客様\u003C/li\u003E\r\n\u003Cli data-anchor=\"resources\"\u003E機械学習に関するリソース\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"experiencefragment":{"id":"experiencefragment-3747f070ef","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/ja/site/share-icons/share-icons-no-title/jcr:content","configured":true,":items":{"root":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container_949147658":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-370b3a4d20",":items":{"container_949147658":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-cad107ab25","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"markup_editor":{"id":"markup-editor-1476d85c25","title":" ","htmlContent":"\u003Cdiv class=\"share-icon-group\"\u003E\r\n\u003Cspan class=\"share-icon share-icon--linkedin\"\u003E\r\n\u003Csvg class=\"share-icon__svg share-icon--linkedin\" viewBox=\"0 0 26 24\" fill=\"none\" xmlns=\"http://www.w3.org/2000/svg\"\u003E\r\n\u003Cpath d=\"M23.741 0H1.89287C0.846282 0 0 0.773438 0 1.72969V22.2656C0 23.2219 0.846282 24 1.89287 24H23.741C24.7876 24 25.6388 23.2219 25.6388 22.2703V1.72969C25.6388 0.773438 24.7876 0 23.741 0ZM7.60653 20.4516H3.80076V8.99531H7.60653V20.4516ZM5.70364 7.43438C4.48179 7.43438 3.4953 6.51094 3.4953 5.37187C3.4953 4.23281 4.48179 3.30937 5.70364 3.30937C6.92049 3.30937 7.90698 4.23281 7.90698 5.37187C7.90698 6.50625 6.92049 7.43438 5.70364 7.43438ZM21.8481 20.4516H18.0473V14.8828C18.0473 13.5563 18.0223 11.8453 16.0693 11.8453C14.0914 11.8453 13.7909 13.2938 13.7909 14.7891V20.4516H9.99515V8.99531H13.6407V10.5609H13.6907C14.1965 9.66094 15.4384 8.70938 17.2862 8.70938C21.137 8.70938 21.8481 11.0813 21.8481 14.1656V20.4516V20.4516Z\" fill=\"#249EDC\"/\u003E\r\n\u003C/svg\u003E\r\n\u003C/span\u003E\r\n\u003Cspan class=\"share-icon share-icon--facebook\"\u003E\u003Csvg class=\"share-icon__svg share-icon--facebook\" viewBox=\"0 0 27 24\" fill=\"none\" xmlns=\"http://www.w3.org/2000/svg\"\u003E\r\n\u003Cpath d=\"M26.2775 12C26.2775 5.37258 20.5381 0 13.4581 0C6.37812 0 0.638672 5.37258 0.638672 12C0.638672 17.9895 5.32652 22.954 11.4551 23.8542V15.4688H8.20013V12H11.4551V9.35625C11.4551 6.34875 13.369 4.6875 16.2971 4.6875C17.6993 4.6875 19.1667 4.92188 19.1667 4.92188V7.875H17.5503C15.9579 7.875 15.4611 8.80008 15.4611 9.75V12H19.0165L18.4482 15.4688H15.4611V23.8542C21.5897 22.954 26.2775 17.9895 26.2775 12Z\" fill=\"#249EDC\"/\u003E\r\n\u003C/svg\u003E\r\n\u003C/span\u003E\r\n\u003Cspan class=\"share-icon share-icon--twitter\"\u003E\u003Csvg class=\"share-icon__svg share-icon--twitter\"  viewBox=\"0 0 25 24\" fill=\"none\" xmlns=\"http://www.w3.org/2000/svg\"\u003E\r\n\u003Cpath d=\"M14.9219 10.1624L23.8565 0H21.7393L13.9814 8.82384L7.78523 0H0.638672L10.0085 13.3432L0.638672 24H2.75599L10.9485 14.6817L17.4921 24H24.6387L14.9214 10.1624H14.9219ZM12.022 13.4608L11.0726 12.1321L3.51889 1.55962H6.77097L12.8669 10.0919L13.8163 11.4206L21.7403 22.5113H18.4882L12.022 13.4613V13.4608Z\" fill=\"#249EDC\"/\u003E\r\n\u003C/svg\u003E\r\n\u003C/span\u003E\r\n\u003Cspan class=\"share-icon share-icon--email\"\u003E\u003Csvg class=\"share-icon__svg share-icon--email\" viewBox=\"0 0 33 24\" fill=\"none\" xmlns=\"http://www.w3.org/2000/svg\"\u003E\r\n\u003Cpath fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M4.41235 0H28.4011C30.4998 0 32.1923 1.70379 32.1923 3.79124V20.2088C32.1923 22.3075 30.4885 24 28.4011 24H4.41235C2.31362 24 0.621094 22.2962 0.621094 20.2088V3.79124C0.621094 1.69251 2.3249 0 4.41235 0ZM28.4011 21.4612C29.1007 21.4612 29.6648 20.897 29.6648 20.1975V3.77995C29.6648 3.08037 29.1007 2.5162 28.4011 2.5162H4.41235C3.71277 2.5162 3.14859 3.08037 3.14859 3.77995V20.1975C3.14859 20.897 3.71277 21.4612 4.41235 21.4612H28.4011Z\" fill=\"#249EDC\"/\u003E\r\n\u003Cpath fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M29.6648 20.1975C29.6648 20.897 29.1007 21.4612 28.4011 21.4612H4.41235C3.71277 21.4612 3.14859 20.897 3.14859 20.1975V3.77995C3.14859 3.08037 3.71277 2.5162 4.41235 2.5162H28.4011C29.1007 2.5162 29.6648 3.08037 29.6648 3.77995V20.1975ZM27.7466 6.49927C28.04 6.17205 28.0174 5.66432 27.6902 5.35966V5.34837C27.363 5.055 26.8552 5.07755 26.5506 5.40477L18.7311 13.9577C18.686 14.0141 18.6296 14.0592 18.5731 14.1156C17.2981 15.3117 15.3009 15.2327 14.1162 13.9577L6.2854 5.39351C5.98075 5.05501 5.47299 5.03242 5.14577 5.33708C4.80727 5.64173 4.7847 6.1495 5.08935 6.47672L10.8327 12.7503L5.6084 17.4217C5.2699 17.7151 5.24733 18.2228 5.5407 18.5613C5.83407 18.8998 6.35311 18.9224 6.68033 18.629L11.9159 13.9464L12.9201 15.0409C13.8454 16.0564 15.0865 16.6093 16.418 16.6093C17.7495 16.6093 18.9906 16.0564 19.9159 15.0409L20.8637 14.0028L26.0428 18.6516H26.0654C26.4039 18.945 26.9117 18.9111 27.205 18.5726C27.4984 18.2341 27.4645 17.7264 27.126 17.433L21.9695 12.818L27.7466 6.49927Z\" fill=\"#249EDC\"/\u003E\r\n\u003C/svg\u003E\u003C/span\u003E\r\n\u003C/div\u003E","jsContent":"const pageURL=window.location.href;document.addEventListener('click',(e)=\u003E{const targetClassesArr=[...e.target.classList];console.log(targetClassesArr);if(targetClassesArr.includes('share-icon--linkedin')){const shareURL=`https://www.linkedin.com/sharing/share-offsite/?url=${pageURL}`;window.open(shareURL,'_blank');}if(targetClassesArr.includes('share-icon--facebook')){const shareURL=`http://www.facebook.com/sharer/sharer.php?u=${pageURL}`;window.open(shareURL,'_blank');}if(targetClassesArr.includes('share-icon--twitter')){const shareURL=`https://twitter.com/intent/tweet?url=${pageURL}`;window.open(shareURL,'_blank');}if(targetClassesArr.includes('share-icon--email')){const shareURL=`mailto:?subject=Check out this news from Snowflake&body=${pageURL}`;window.open(shareURL);}});","cssUrl":"/content/experience-fragments/snowflake-site/language-masters/ja/site/share-icons/share-icons-no-title/_jcr_content/root/container_949147658/markup_editor.b96624f84f9291cc.css",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["markup_editor"],":type":"snowflake-site/components/container"}},":itemsOrder":["container_949147658"],":type":"snowflake-site/components/container"},"cq:LiveSyncConfig":{"cq:isDeep":true,"cq:rolloutConfigs":[],"cq:master":"/content/experience-fragments/snowflake-site/language-masters/ja/site/share-icons/share-icons",":type":"cq:LiveCopy"}},":itemsOrder":["root","cq:LiveSyncConfig"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment","appliedCssClassNames":"snowflake-responsive-component-top-padding-extra-small"}},":itemsOrder":["text","experiencefragment"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"fundamentals-main-content","appliedCssClassNames":"snowflake-responsive-container-inner-padding-large",":items":{"container_copy":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"overview","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-0d96a84ba6","additionalClasses":"headline-decoration","type":"heading2","lines":["概要"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-d62a457215","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/\" target=\"_self\"\u003E機械学習\u003C/a\u003E（ML）が現代のテクノロジー構造を根本から刷新した事実は広範に認められています。コードとして事前に記述されたルールを適用するのではなく、学習データを与えることで機械自体に予測や識別を行わせるアプローチは、多様な実用アプリケーションの実現を可能にしました。医療における画像診断システムから電子メールのスパムフィルタ、自動運転支援システムに至るまで、多様な領域で機械学習モデルが活用されています。\u003C/p\u003E\r\n\u003Cp\u003Eさらに、機械学習は\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/fundamentals/large-language-model/\" target=\"_self\"\u003E大規模言語モデル\u003C/a\u003E（LLM）をはじめ、そこから派生する各種\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/generative-ai/\" target=\"_self\"\u003E生成AI\u003C/a\u003Eアプリケーションを支えるコア技術としての役割も担っています。しかし、\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/models/\" target=\"_self\"\u003EMLモデル\u003C/a\u003Eの構築と学習プロセスには膨大な時間と計算リソースが必要であり、インフラストラクチャへの投資に加え、高度なAIやデータサイエンスの専門知識が求められます。こうした課題に対し、モデル構築プロセスの多くを自動化するAutoML（Automated Machine Learning）が登場し、データサイエンティストやデータエンジニアのみならず、ビジネスアナリストや現場のユーザー層からも広く採用されています。\u003C/p\u003E\r\n\u003Cp\u003EAutoMLは専門チームとビジネス現場における技術ギャップを埋め、企業全体での\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/\"\u003EAI\u003C/a\u003E活用とスケーラビリティの向上を推進します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy_":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container_copy_copy__480869401":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__373061683":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1444615495":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy_":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__455068363":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__659376865":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1500909857":"aem-GridColumn aem-GridColumn--default--12","container_copy_copy__1978652079":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"rel","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"container_copy_copy":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"what","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-27bfe21976","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoMLとは"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-88db2a7114","text":"\u003Cp\u003EAutoMLは、機械学習モデルの構築における一連の中核プロセスである、最適なアルゴリズムの選定、ハイパーパラメータの調整、生データをモデルが処理可能な形式へ変換する\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/feature-engineering/\"\u003E特徴量エンジニアリング\u003C/a\u003Eなどをソフトウェアによって自動処理する技術です。この自動化により、従来であればデータエンジニアやデータサイエンティストが数ヶ月を要していたモデル構築期間を、数日ないし数時間にまで大幅に短縮することが可能となります。また、高度なAIや機械学習の専門知識を要さずとも、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/solutions/industries/healthcare-and-life-sciences/\"\u003E医療・ヘルスケア\u003C/a\u003E、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/solutions/industries/financial-services/\"\u003E金融\u003C/a\u003E、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/solutions/departments/marketing/\"\u003Eマーケティング\u003C/a\u003Eといった各事業部門のユーザー自身が実務に適したモデルを構築できる環境を整え、組織全体におけるAI運用の定着と民主化を推進します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy_":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"benefits","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-05ea8466a0","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoMLがモデル構築に革新をもたらす主な要因"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-8e21157ef7","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EAutoMLは、従来の機械学習モデル構築におけるプロセスやアプローチを以下の側面から刷新します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E開発の民主化：\u003C/b\u003EAutoMLは高度な技術的参入障壁を取り除きます。これにより、データサイエンスの専門知識を持たない各事業部門のドメインエキスパートであっても、実用的なモデルを構築することが可能になります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E生産性の向上：\u003C/b\u003E特徴量エンジニアリング、アルゴリズムの選定、ハイパーパラメータの調整といった手作業による試行錯誤を自動化することで、モデル開発ライフサイクル全般の所要時間を大幅に削減します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E予測精度の向上：\u003C/b\u003EAutoML基盤は、広大な探索空間から何百ものアルゴリズムとパラメータの組み合わせを体系的に検証します。これにより、手動による設計では見落とされがちな、より高い予測性能を持つモデル構造の選定を可能にします。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E再現性の強化：\u003C/b\u003EAutoMLプラットフォームは、モデリングの試行過程における設定、選定アルゴリズム、およびハイパーパラメータを自動的に記録し、明確な監査証跡を生成します。これにより、検証結果の確実な再現性を担保し、モデル構築ロジックの透明性を確保します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E標準化と一貫性の担保：\u003C/b\u003Eモデルの検証、交差検証、および評価手法の適用手順を標準化します。手作業に伴う設定ミスやロジックの不整合といったヒューマンエラーを排除し、予測精度を損なうリスクを最小化します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1444615495":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"components","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-065a74c048","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoMLパイプラインを構成する主要コンポーネント"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-cca1db8db2","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EAutoMLパイプラインの主要なコンポーネントを以下に紹介します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eデータの前処理\u003C/h3\u003E\r\n\u003Cp\u003Eモデル学習の前段階として、欠損値の補完、外れ値の除去、およびデータ型の変換を実行し、生データのクレンジングと整形を行います。モデルトレーニングの開始前に\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/fundamentals/a-practical-guide-to-data-quality/\"\u003Eデータ品質\u003C/a\u003Eと整合性を担保します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E特徴量エンジニアリング\u003C/h3\u003E\r\n\u003Cp\u003E新規変数の生成、カテゴリ別データのエンコーディング、数値特徴量のスケーリング、ならびに予測寄与度の高い変数のみを選択する特徴量選択を通じて生データを最適化し、モデルの予測精度を向上させます。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eアルゴリズムモデルの選択\u003C/h3\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/models/decision-tree/\"\u003E決定木\u003C/a\u003E、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/neural-network/\"\u003Eニューラルネットワーク\u003C/a\u003E、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/ensemble-learning/\"\u003Eアンサンブル学習\u003C/a\u003Eなど、複数の機械学習アルゴリズムを体系的に比較検証します。与えられたデータセットとビジネス課題に対して最も適したアプローチを特定します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eトレーニング\u003C/h3\u003E\r\n\u003Cp\u003Eモデルがデータ内に潜むパターンや相関関係を識別できるよう、ラベル付きの学習データ（例：「スパム」「正常」として分類された電子メールなど）を大量に処理させるプロセスです。モデルはこのプロセスで獲得した汎用的なパターンに基づき、未学習のデータに対しても高精度な分類や予測を実行します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eアンサンブル学習\u003C/h3\u003E\r\n\u003Cp\u003E同一のデータセットに対して複数の異なる機械学習アルゴリズムやモデルを個別に学習させ、それぞれの予測結果を統合（平均化または多数決など）して最終的な判定を導き出す手法です。単一モデルに固有のバイアスや過学習リスクを緩和し、より平滑化された堅牢な予測性能を実現します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eハイパーパラメータの最適化\u003C/h3\u003E\r\n\u003Cp\u003E学習率、決定木の深さ、正則化パラメータなど、各アルゴリズムの学習挙動を制御するハイパーパラメータ群を自動的にファインチューニングし、最も性能の出やすいパラメータセットの組み合わせを特定します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E評価と検証\u003C/h3\u003E\r\n\u003Cp\u003E構築されたモデルが未知のデータに対しても高い汎化性能を発揮するかを評価します。交差検証をはじめとする評価手順を適用し、過学習（学習データのみに過剰適合し、未知データに対する汎化性能が著しく低下する現象）やモデルの偏りを検出しながら、適合率、再現率、正解率といった各種評価指標を算出します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eデプロイメントとモニタリング\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLは、評価結果に基づき本番環境へのデプロイに最適なモデルを自動的に選定し、稼働後のモデルパフォーマンスを継続的に監視するモニタリング環境を構築します。データ構造やビジネス環境の経時的変化に伴うモデルのドリフトを早期に検知し、必要に応じてモデルの自動再学習手順を起動することで、長期的な予測精度を維持します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E説明可能性の確保\u003C/h3\u003E\r\n\u003Cp\u003Eビジネスへの影響度が高い領域では、モデルの意思決定プロセスが不透明なブラックボックス状態を回避し、特定の判定に至った根拠を客観的に説明できる透明性が求められます。多くのAutoML基盤には、データの前処理ロジック、アルゴリズム選定の根拠、ならびに各特徴量が予測結果へ与えた影響度を自動で可視化する説明可能性ツールが実装されています。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1978652079":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"use-cases","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-c9ae40c85a","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoMLの代表的な6つのユースケース"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-e94719c6ea","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003E機械学習モデルの活用は広範な業界に及んでおり、AutoMLを導入することで組織におけるMLイニシアチブの実装速度とROIを大幅に向上させることが可能です。AutoMLが特に有効性を発揮する代表的なユースケースは以下の通りです。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E1.売上、需要予測\u003C/h3\u003E\r\n\u003Cp\u003E過去の販売実績データ、季節変動要因、および市場トレンドを複合的に分析する\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/en/fundamentals/sales-forecasting/\"\u003E売上予測\u003C/a\u003Eモデルの構築を自動化します。データサイエンスチームに個別で分析を依頼することなく、このような\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/fundamentals/predictive-analytics/\"\u003E予測分析\u003C/a\u003Eに基づいて、在庫の最適化、要員計画、予算配分などを迅速に調整することが可能になります。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E2.不正利用の検知\u003C/h3\u003E\r\n\u003Cp\u003E金融機関や決済サービス事業者は、リアルタイムに\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/solutions/industries/financial-services/fraud-detection-and-financial-crimes/\"\u003E不正の疑いがあるトランザクション\u003C/a\u003Eを特定するために機械学習モデルを活用しています。攻撃手法や不正スキームが多様化、高度化し続ける環境下において、AutoMLの導入によりリスク管理部門や不正分析担当者は高精度な検知モデルを迅速に構築でき、脅威の進化へ即時に追従することが可能となります。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E3.解約（チャーン）の予測\u003C/h3\u003E\r\n\u003Cp\u003Eサブスクリプション型サービスや\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/solutions/industries/telecom/\" target=\"_self\"\u003E通信\u003C/a\u003Eなどの事業者は、サービスを解約するリスクが高い顧客層の兆候を事前に察知するために機械学習を活用しています。AutoMLによって、市場環境やユーザー行動パターンの変動に対応した最新のチャーン予測モデルを短サイクルでテストおよび本番デプロイできるようになり、解約防止に向けた実効性の高い積極的なアプローチを実現します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E4.疾患診断、医療データの解析\u003C/h3\u003E\r\n\u003Cp\u003E医療機関では、画像診断データ、臨床検査結果、問診データなどの多角的な医療データを機械学習モデルで解析し、医師の診断精度向上および最適な治療アプローチの立案を支援しています。新たな臨床研究成果や症例データが蓄積された場合でも、AutoMLを活用することでモデルの継続的なアップデートおよび精度の再調整をシームレスに行うことが可能です。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E5.在庫管理、需給の最適化\u003C/h3\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/solutions/industries/retail-consumer-goods/\"\u003E小売企業\u003C/a\u003Eでは、店舗や物流拠点ごとの特定商品における需要を精密に予測し、適切な品揃えと仕入れのタイミングを維持するためにモデルを活用しています。AutoMLを導入することで、商品カテゴリ別や地域拠点別といった膨大な数の個別モデルを迅速に並列構築することが可能となります。市場環境やトレンドの変動に応じてモデルの再学習も自動化されるため、欠品リスクの低減と過剰在庫の抑止を両立させます。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E6.ダイナミックプライシングの実装\u003C/h3\u003E\r\n\u003Cp\u003EEコマースやライドシェアリングなどのサービス領域において、AutoMLはリアルタイムに流入する需要と供給のデータストリームを組み込んだダイナミックプライシングモデルの構築を可能にします。さまざまな地域、製品ライン、サービス帯において異なる価格戦略のA/Bテストや効果検証を短サイクルで試行できるため、運用担当者による手動の価格調整を介すことなく、収益の最大化と市場適応力の向上を実現します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__455068363":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"limitations","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-2758b82cc9","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoML導入における主な制限事項と課題"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-37a50fe976","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EAutoMLプラットフォームは、モデル構築プロセスの自動化、設定ミスなどのヒューマンエラー防止、データサイエンスチームの高度タスクへのシフト、ならびに全社的なAI運用の定着など、エンタープライズに多様な実益をもたらします。一方で、システムの構造に起因する固有の制約や運用上の制限事項が存在することも把握しておく必要があります。代表的な制約事項は以下の通りです。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E高度な個別ドメイン課題に対する汎用アプローチの限界\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLは標準化されたアルゴリズム群や特徴量抽出ロジックを優先的に適用する設計となっているため、特定の業界や特殊な業務要件が絡む課題に対しては最適化しきれないケースが存在します。該当領域のドメインエキスパートが手動で設計やチューニングする高度なカスタムモデリング手法と比較した場合、特定の課題に固有の成果を引き出しにくい側面があります。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eビジネスコンテキストおよびドメイン知識の欠如\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLシステムは純粋な統計的、数理的アプローチに基づいて処理を行うため、特定の業界におけるビジネスコンテキストや実務知識を自発的に理解することはできません。業界特有の季節変動パターン、商習慣に基づく不連続なデータ構造、あるいは規制上の制約事項といった、人間の専門家であれば考慮すべき重要なコンテキストや定性的なニュアンスをモデル構築ロジックへ自動的に反映させることには限界があります。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eデータ品質への直接的な依存\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLプラットフォームを導入した場合でも、「質の低い入力データからは質の低い出力しか得られない」という機械学習の本質的な課題を回避することはできません。入力データ自体にバイアスが含まれている場合や、欠損や不整合が著しいデータ、目的にそぐわない無関連なデータを読み込ませた場合、自動化されたパイプラインであっても信頼性の低い予測モデルしか生成できません。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003E柔軟性の制約とカスタマイズの限界\u003C/h3\u003E\r\n\u003Cp\u003Eプラットフォームが提供する自動化パイプラインの適用範囲を超えた、特殊な処理ロジック、独自のカスタムアルゴリズム、あるいは高度に複雑なデータ前処理などを実装する際、一定の技術的制約に直面する場合があります。そのため、高度な要件を求めるMLエンジニアやエキスパートによる自由なパイプライン拡張が難しくなるケースが存在します。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eドメイン特有の特徴量生成における制約\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLは標準的な補正、エンコーディング、スケーリングなどの特徴量エンジニアリングには対応しているものの、特定の事業ドメインや業務ロジックに深く依存する複雑な特徴量生成を網羅的に捉えきれない場合があります。こうした手動による設計が排されることで、モデルの潜在的な予測性能を引き出しきれないリスクが生じます。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eモデルのブラックボックス化\u003C/h3\u003E\r\n\u003Cp\u003EAutoMLは単一のシンプルなモデルであれば判断プロセスの解説が可能ですが、複数のモデルを組み合わせる複雑なアンサンブル手法などが適用された場合、その内部ロジックや特定の予測に至った根拠を人間が直感的に解釈することは極めて困難になります。このブラックボックス化の問題は、厳格な監査対応や意思決定の透明性が必須とされる、金融機関における融資審査や医療診断といった領域への適用において制約となります。\u003Cbr\u003E\r\n\u003C/p\u003E\r\n\u003Ch3\u003Eベンダーロックインのリスクと移行コストの増大\u003C/h3\u003E\r\n\u003Cp\u003E多くの商用AutoMLプラットフォームは、ライセンスコストや運用費が高額になる傾向があるだけでなく、特定の商用基盤など独占的な仕様に強く依存する構造を生み出しがちです。これにより、構築したモデルを自社の異なるインフラ環境へ移行することや、外部依存を排して独立して維持管理することが困難になるケースがあります。\u003C/p\u003E\r\n\u003Cp\u003Eこうした制約からも、AutoMLはデータサイエンティストや専門人材を完全に置き換えるものではなく、人間の専門性とドメイン知識を強力に拡張するツールとして位置付けるのが最も効果的です。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__659376865":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"conclusion","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-7446a08e5d","additionalClasses":"headline-decoration","type":"heading2","lines":["結論"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"text":{"id":"text-2d0f4f7e73","additionalClasses":"list--blue-bullets","text":"\u003Cp\u003EAutoMLは、高度な専門知識を持たない各部門のドメインエキスパートによる高精度な予測モデル構築を可能にし、機械学習の全社的な定着と民主化を実現します。従来のモデル開発に要していた数ヶ月単位の試行期間を数日レベルへ短縮し、エンタープライズにおけるAI活用と価値創出を大きく加速させます。\u003C/p\u003E\r\n\u003Cp\u003E膨大なアルゴリズムとパラメータの組み合わせを短時間で体系的に試行することで、最高水準の汎化性能を持つ最適なモデル構成を迅速に特定します。同時に、モデルの評価プロセスにおける標準化されたベストプラクティスを機械的に適用することにより、予測精度やガバナンスを損なう人的エラーを未然に防止します。\u003C/p\u003E\r\n\u003Cp\u003Eしかしながら、AutoMLの導入にあたってはいくつかの制約事項を十分に考慮する必要があります。具体的には、ドメイン固有のビジネスコンテキストや背景知識の欠如、モデルのブラックボックス化に伴う説明可能性の課題、さらには入力データ品質への強い依存性が挙げられます。\u003C/p\u003E\r\n\u003Cp\u003E適切な\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/data-governance/\"\u003Eデータガバナンス\u003C/a\u003E、強固なデータインフラストラクチャ、および専門人材による監視を前提とした運用体制を整備することで、AutoMLは人間の高度な専門性を補完し、エンタープライズ全社におけるAIイニシアチブの推進とスケーラビリティの向上を実現する強力なコアツールとなります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05 snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","text"],":type":"snowflake-site/components/container"},"container_copy_copy__1500909857":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"title_v2":"aem-GridColumn aem-GridColumn--default--12","simple_snowflake_acc":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"faq","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-f29c07b8dc","additionalClasses":"headline-decoration","type":"heading2","lines":["AutoMLに関するよくある質問"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"simple_snowflake_acc":{"id":"simple-snowflake-accordion-3e79f71558","showDivider":false,"accordionItemsList":[{"title":"機械学習（ML）とAutoMLの違いは何ですか？","richText":"\u003Cp\u003E機械学習（Machine Learning）は、コンピューターにデータ内のパターンを学習させ、予測や判断を行わせる広義の技術、学問分野全般を指します。一方、AutoML（Automated Machine Learning）は、アルゴリズムの選定やハイパーパラメータの調整といった、機械学習モデルの構築における複雑で時間のかかる一連の手順を自動化するツール基盤です。\u003C/p\u003E\r\n\u003Cp\u003E基本概念として、機械学習がデータ科学の理論および技術そのものであるのに対し、AutoMLはそのモデリングプロセスを自動化し、データサイエンティスト以外のドメインエキスパートやビジネスユーザーであっても高度なモデルを活用可能にする実践的な技術セットと位置付けられます。\u003C/p\u003E\r\n"},{"title":"MLOpsとAutoMLの違いは何ですか？","richText":"\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/machine-learning/mlops/\" target=\"_self\"\u003EMLOps\u003C/a\u003E（Machine Learning Operations）は、構築されたモデルの本番環境へのデプロイ、稼働監視、データドリフト検知、再学習といったモデルライフサイクル全般の継続的な管理に焦点を当てた運用体系および手法を指します。一方、AutoML（Automated Machine Learning）はモデル構築の初期段階（データの前処理、アルゴリズムの選定、ハイパーパラメータ調整、モデル学習）を自動化する技術を指します。\u003C/p\u003E\r\n\u003Cp\u003E要約すると、MLOpsは「構築されたモデルが市場やビジネス環境の変化に応じて本番環境で安定して稼働し続けることを保証する運用プラットフォーム」であり、AutoMLは「高品質なモデルを迅速に構築するための自動化手法」として相補的な役割を果たします。\u003C/p\u003E\r\n"},{"title":"AutoMLプラットフォームはどのように選べばよいですか？","richText":"\u003Cp\u003E選定は、既存のデータ基盤との距離、自動化の範囲、カスタマイズの自由度の3点で判断します。\u003C/p\u003E\r\n\u003Cp\u003Eデータがすでにクラウド上にある場合は、Amazon SageMaker Autopilot、Google Vertex AI AutoML、Microsoft Azure Machine Learningなど、同一クラウド内に統合されたAutoML基盤がデータ移動のコストと手間を最小化します。一方、複数のデータソースをまたぐ場合や高度な\u003Ca href=\"https://www.snowflake.com/ja/artificial-intelligence/ai-governance/model-governance/\" target=\"_self\"\u003Eモデルガバナンス\u003C/a\u003E要件がある場合は、DataRobot、H2O.ai（Driverless AI）、IBM Watsonといった専門ベンダーのプラットフォームが、監査ログや説明可能性の機能を標準で備えています。\u003C/p\u003E\r\n\u003Cp\u003E特徴量エンジニアリングを自前で作り込む必要がある場合は、Auto-sklearn、TPOT、AutoGluonなどのオープンソースライブラリが選択肢になります。\u003Ca href=\"https://scikit-learn.org/stable/index.html\" target=\"_blank\" rel=\"noopener noreferrer\"\u003EScikit-learn\u003C/a\u003EやPyTorchのワークフローを自動化しながら、処理の各段階に介入できる自由度が残ります。\u003C/p\u003E\r\n"},{"title":"AutoMLの導入にはどれくらいのコストがかかりますか？","richText":"\u003Cp\u003EAutoMLのコストは、ライセンス費用ではなく学習に使う計算リソース量で決まる構造が主流です。\u003C/p\u003E\r\n\u003Cp\u003Eクラウドベンダーが提供するAutoML基盤は、モデルの探索と学習に使ったコンピュート時間に対する従量課金が一般的です。AutoMLは複数のアルゴリズムとハイパーパラメータの組み合わせを並列に試行するため、手作業でモデルを1つ構築する場合よりも計算量は増えます。そのぶん人的工数は大幅に削減されるため、コスト評価はデータサイエンティストの人件費と計算リソース費を合わせた総額で行う必要があります。\u003C/p\u003E\r\n\u003Cp\u003EオープンソースのAutoMLライブラリはライセンス費用が発生しませんが、実行環境の構築と運用を自社で担うことになります。また探索範囲の上限や試行回数の制限を設定できるプラットフォームであれば、予算に合わせて計算コストを制御できます。データが保管されている場所でそのまま学習を実行できる構成にすれば、データ移動に伴う転送コストと重複ストレージのコストも回避できます。\u003C/p\u003E\r\n"},{"title":"AutoMLはどのように進化していますか？","richText":"\u003Cp\u003E現在のAutoMLは、基盤モデルや大規模言語モデル（LLM）との統合へと進化を遂げています。ゼロからモデルを構築するアプローチから、事前学習済みモデルの自動ファインチューニングや、プロンプト、特徴量生成の自動化へとシフトしつつあります。\u003C/p\u003E\r\n\u003Cp\u003Eさらに近年では、\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/computer-vision/\" target=\"_self\"\u003Eコンピュータービジョン\u003C/a\u003E、自然言語処理（\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/fundamentals/natural-language-processing/\" target=\"_self\"\u003ENLP\u003C/a\u003E）、時系列予測などの専門分野に特化したドメイン固有のAutoML機能が拡充される一方で、モデルの予測根拠を明示する説明可能性、\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/ai-governance/ai-ethics/\" target=\"_self\"\u003EAI倫理\u003C/a\u003Eや\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/artificial-intelligence/ai-governance/ai-fairness/\" target=\"_self\"\u003E公平性\u003C/a\u003Eへの配慮、および自動化処理と人間の専門知識や監視を融合させるHuman-in-the-loopアプローチの実装に重点が置かれています。\u003C/p\u003E\r\n"},{"title":"AutoMLを導入すればデータサイエンティストは不要になりますか？","richText":"\u003Cp\u003E不要にはなりません。AutoMLが自動化するのはモデル構築の反復作業であり、その前後に残る判断は専門人材の領域です。\u003C/p\u003E\r\n\u003Cp\u003EAutoMLが引き受けるのは、アルゴリズムの選定、ハイパーパラメータの調整、複数モデルの比較といった試行錯誤の工程です。一方で、どの業務課題を機械学習で解くべきかの設定、目的変数の定義、ビジネス上の仮説に基づく特徴量の設計、そして出力されたモデルを業務判断に使ってよいかの妥当性評価は、ドメイン知識と統計的な判断力を前提とします。これらはAutoMLの自動化範囲の外にあります。\u003C/p\u003E\r\n\u003Cp\u003E実務上の変化は、専門人材の役割が「モデルを作る人」から「課題設定とモデルの妥当性を保証する人」へ移ることです。同時に、AutoMLによってデータアナリストや業務部門の担当者もモデル構築に参加できるようになるため、専門人材が対応できる案件の総数が増えます。\u003C/p\u003E\r\n"},{"title":"AutoMLを使うにはどれくらいのデータ量が必要ですか？","richText":"\u003Cp\u003E必要なデータ量は解く問題の種類によりますが、表形式データの予測タスクであれば数千行規模から実用的なモデルが得られます。\u003C/p\u003E\r\n\u003Cp\u003EAutoMLは複数のアルゴリズムを比較するために学習データを分割して検証を繰り返すため、手作業で1つのモデルを作る場合よりも多めのデータがあるほうが結果が安定します。目安として、分類タスクでは予測したいクラスごとに数百件以上のサンプルを確保できると、精度の評価が信頼できる水準になります。不正検知のように該当データが極端に少ない不均衡なケースでは、件数そのものより少数クラスの絶対数が制約になります。\u003C/p\u003E\r\n\u003Cp\u003E一方で、データ量よりも品質のほうが結果を左右します。欠損や表記の不統一、収集時点のばらつきがあるデータでは、量を増やしても精度は上がりません。AutoMLは前処理の一部を自動化しますが、データそのものの正確性を補うことはできないため、投入前の整備が前提になります。\u003C/p\u003E\r\n"}],":type":"snowflake-site/components/simple-snowflake-accordion","appliedCssClassNames":"snowflake-responsive-component-bottom-padding-small"}},":itemsOrder":["title_v2","simple_snowflake_acc"],":type":"snowflake-site/components/container"},"container_copy_copy__480869401":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"customer","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-cec3fba9e5","additionalClasses":"headline-decoration","type":"heading2","lines":["Snowflakeの機械学習をご利用のお客様"],":type":"snowflake-site/components/title-v2","appliedCssClassNames":"snowflake-responsive-component-top-padding-none"},"flexible_column_cont":{"id":"flexible-column-container-c026a2418e","type":"2-column-even","alignColumns":"match-height","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"small","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-eb0684a559","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"card_v2":{"id":"card-v2-37406796bd","configurationStatus":{"configured":true,"message":""},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/customers/all-customers/case-study/cyberagent/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"活用事例を読む"},"title":{"id":"title","type":"heading4","lines":["サイバーエージェント：AIによる予測を価格戦略に活用"],":type":"snowflake-site/components/title-v2"},"image":{"id":"image","height":"351","alt":"CyberAgent","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--8868c0fb-d91f-4eea-b561-d5c48c5f5099/cyberagent%25403x.png?quality=85&preferwebp=true","width":"624",":type":"snowflake-site/components/image"},"type":"content-card","text":{"id":"text","text":"\u003Cp\u003E購買データから値引き対象や金額を予測する「価格エージェント」の事例です。Snowflake Native App FrameworkとStreamlit in Snowflakeを活用し、顧客がAIモデルによるシミュレーションを利用できる仕組みを提供しています。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-bb1b2a34de","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"card_v2_copy":{"id":"card-v2-8191403290","configurationStatus":{"configured":true,"message":""},"button":{"id":"button","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/customers/all-customers/case-study/mitsui-sumitomo-trust-asset-management/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"活用事例を読む"},"title":{"id":"title","type":"heading4","lines":["三井住友トラスト・アセットマネジメント：生成AIアプリを短期間で実装"],":type":"snowflake-site/components/title-v2"},"image":{"id":"image","height":"351","alt":"三井住友トラスト・アセットマネジメント","isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--2746eaf5-7246-4655-9c44-35e57fc77572/mitsui-sumitomo-trust-asset-management.png?quality=85&preferwebp=true","width":"624",":type":"snowflake-site/components/image"},"type":"content-card","text":{"id":"text","text":"\u003Cp\u003E各社の決算資料に基づいて質問に回答するチャットボットを、Snowflake Cortex AIを活用してわずか2〜3日で実装した事例をご覧いただけます。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text"},"layoutStyle":"vertical",":type":"snowflake-site/components/card-v2"}},":itemsOrder":["card_v2_copy"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false}},":itemsOrder":["title_v2","flexible_column_cont"],":type":"snowflake-site/components/container"},"container_copy_copy__373061683":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12","title_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"resources","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"title_v2":{"id":"title-v2-87ec2c482f","type":"heading2","lines":["機械学習に関するリソース"],":type":"snowflake-site/components/title-v2"},"flexible_column_cont":{"id":"flexible-column-container-ab9d0cca4c","type":"2-column-even","alignColumns":"top","containerMaxWidth":"extra-large","topPadding":"extra-small","bottomPadding":"none","spaceBetween":"small","reverseOnMobile":false,"carouselOnMobile":false,"backgroundImageOption":"none","flexible_column_content_container_1":{"layout":"SIMPLE","id":"container-60949714e5","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"content_chip_copy_co":{"id":"content-chip-a330d5f442","tagText":"プロダクト","tagColor":"#29B5E8","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/product/ai/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"ソリューションを確認する"},"headline":{"id":"title","type":"heading5","lines":["生成AIのためのSnowflake"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"},"content_chip_copy_co_158246178":{"id":"content-chip-3b0f36bcd6","tagText":"機能","tagColor":"#29B5E8","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/product/features/end-to-end-ml-workflows/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"機能を詳しく知る"},"headline":{"id":"title","type":"heading5","lines":["Snowflake ML"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"},"content_chip_copy_co_271648072":{"id":"content-chip-b9eb89edb4","tagText":"ウェビナー","tagColor":"#EEBDD3","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/webinars/customer-webinars/rapid-customer-insights-with-scalable-ml-workflows-in-snowflake-2025-08-28/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"今すぐ登録"},"headline":{"id":"title","type":"heading5","lines":["Rapid Customer Insights with Scalable ML Workflows in Snowflake"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"}},":itemsOrder":["content_chip_copy_co","content_chip_copy_co_158246178","content_chip_copy_co_271648072"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"flexible_column_content_container_2":{"layout":"SIMPLE","id":"container-4202bac18c","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"content_chip_copy_co":{"id":"content-chip-0e6bfe3bf9","tagText":"アカデミー","tagColor":"#99AEB5","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/data-cloud-academy-generative-ai-llm/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"今すぐ登録"},"headline":{"id":"title","type":"heading5","lines":["Generative AI & ML School"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"},"content_chip_copy_co_836268272":{"id":"content-chip-d08e1bcaab","tagText":"機能","tagColor":"#29B5E8","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/product/features/arctic/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"機能を詳しく知る"},"headline":{"id":"title","type":"heading5","lines":["Arctic"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"},"content_chip_copy_co_696221224":{"id":"content-chip-5d779b9c1f","tagText":"eBook","tagColor":"#71D3DC","cta":{"id":"cta","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/ja/lp/radical-roi-generative-ai/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"eBookをダウンロード"},"headline":{"id":"title","type":"heading5","lines":["2026年 生成AIとエージェントのROI"],":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/content-chip"}},":itemsOrder":["content_chip_copy_co","content_chip_copy_co_836268272","content_chip_copy_co_696221224"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false}},":itemsOrder":["title_v2","flexible_column_cont"],":type":"snowflake-site/components/container"}},":itemsOrder":["container_copy_copy","container_copy_copy_","container_copy_copy__1444615495","container_copy_copy__1978652079","container_copy_copy__455068363","container_copy_copy__659376865","container_copy_copy__1500909857","container_copy_copy__480869401","container_copy_copy__373061683"],":type":"snowflake-site/components/container"},"markup_editor":{"id":"markup-editor-9ca16ee0a8","title":"Page CSS","jsContent":"window.addEventListener('click',(e)=\u003E{if(e.target.tagName==='LI'&&e.target.dataset.anchor){const target=document.getElementById(e.target.dataset.anchor);if(target){const targetPosition=target.getBoundingClientRect().top+window.pageYOffset-220;window.scrollTo({top:targetPosition,behavior:'smooth'});}}});","cssUrl":"/content/snowflake-site/global/ja/artificial-intelligence/machine-learning/automl/_jcr_content/root/responsivegrid/container/container/flexible_column_cont/flexible_column_content_container_2/markup_editor.a8023bb6331ec521.css",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["container_copy","container_copy_copy_","markup_editor"],":type":"snowflake-site/components/flexible-column-container/flexible-column-content-container"},"isActiveTOC":false,":type":"snowflake-site/components/flexible-column-container","isBlogPage":false},"related_content":{"id":"related-content-8d9dab5729","relatedContent":[{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["What Is Random Forest in Machine Learning?"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/random-forest/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"What Is Random Forest in Machine Learning?"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["What Is Feature Extraction in Machine Learning?"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/feature-extraction-machine-learning/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"What Is Feature Extraction in Machine Learning?"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["Data Governance Framework: Everything You Should Know"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/data-governance/frameworks/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Data Governance Framework: Everything You Should Know"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["Automated Data Processing (ADP): A Guide to Efficiency"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/automated-data-processing/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Automated Data Processing (ADP): A Guide to Efficiency"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["Machine Learning Frameworks: Features, Use Cases, Selection"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/machine-learning-frameworks/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Machine Learning Frameworks: Features, Use Cases, Selection"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["What Is Anomaly Detection? Key Components and Techniques"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/anomaly-detection/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"What Is Anomaly Detection? Key Components and Techniques"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["What is Data Orchestration? A Guide to Modern Pipelines"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/data-orchestration/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"What is Data Orchestration? A Guide to Modern Pipelines"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["What Is an Operational Data Store (ODS)? Complete Guide"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/a-modern-approach-to-the-operational-data-store/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"What Is an Operational Data Store (ODS)? Complete Guide"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"title":{"lines":["Customer Data Platform (CDP): Benefits, Types, Requirements"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-0f508421a7","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"https://www.snowflake.com/en/fundamentals/customer-data-platform/"},"linkTargetContentType":"GENERIC",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_EXTERNAL","text":"Customer Data Platform (CDP): Benefits, Types, Requirements"},":type":"snowflake-site/components/blog/card"}],":type":"snowflake-site/components/blog/related-content","isBlogPage":false,"appliedCssClassNames":"snowflake-responsive-component-bottom-padding-medium"}},":itemsOrder":["flexible_column_cont","related_content"],":type":"snowflake-site/components/container"}},":itemsOrder":["container"],":type":"snowflake-site/components/container"}},":itemsOrder":["breadcrumb","hero_system","container"],":type":"wcm/foundation/components/responsivegrid"},"modal_container":{"layout":"SIMPLE","id":"container-239f7880a9",":items":{},":itemsOrder":[],":type":"snowflake-site/components/modal/modal-container"},"experiencefragment-footer":{"id":"experiencefragment-75db597db9","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/ja/site/footer/master/jcr:content","configured":true,":items":{"root":{"additionalClasses":"sf-footer","layout":"SIMPLE","id":"container-4351c635d0","appliedCssClassNames":"ui-background-02",":items":{"container_copy_811922734":{"additionalClasses":"sf-footer__inner","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-5a6a2156f4","appliedCssClassNames":"snowflake-container snowflake-responsive-container-inner-padding-small",":items":{"flexible_column_cont":{"id":"flexible-column-container-540fb3721b","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-b0eaa26be7",":items":{"container":{"additionalClasses":"sf-footer-grid__inner","layout":"RESPONSIVE_GRID","columnCount":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"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-c076e6f871","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"container_1622723482":{"additionalClasses":"sf-footer__column","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-d5c29cee26","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"container":{"additionalClasses":"sf-footer__newsletter-group","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12","marketo_v2":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-7b271cae75","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"text":{"id":"text-2cce647dfa","additionalClasses":"sf-footer__newsletter-title","text":"\u003Cp\u003E\u003Cb\u003Eマンスリーニュースレターを購読する\u003C/b\u003E\u003C/p\u003E\r\n\u003Cp\u003ESnowflakeの製品に関する最新情報、専門家の知見、役立つリソースを直接お届けします。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-04"},"marketo_v2":{"id":"marketo-v2-1047674316","marketoForm":{"hidden":null,"successUrl":null,"formId":"45871","edit":false,"script":null,"values":null},"marketoConfigured":true,"serverInstance":"252-RFO-227.mktoweb.com","munchkinId":"252-RFO-227","formConfigured":true,"partnerCampaignPage":false,":type":"snowflake-site/components/form/marketo-v2"}},":itemsOrder":["text","marketo_v2"],":type":"snowflake-site/components/container"}},":itemsOrder":["container"],":type":"snowflake-site/components/container"},"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text_copy":"aem-GridColumn aem-GridColumn--default--12","text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-15139157a9","appliedCssClassNames":"snowflake-responsive-container-inner-padding-medium",":items":{"text":{"id":"text-9c6071d87f","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003Eプロダクト\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/product/platform/\"\u003Eプラットフォーム\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/product/data-engineering/\"\u003E データエンジニアリング\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/product/analytics/\"\u003E分析\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/product/ai/\"\u003EAI\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/product/applications-and-collaboration/\"\u003Eアプリケーションとコラボレーション\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/pricing-options/\"\u003E料金 \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-224ba7b0a3","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003Eサポート\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/support/\"\u003Eサポート（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/en/support/\"\u003E優先サポート（英語） \u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://status.snowflake.com/\" target=\"_blank\" rel=\"noopener noreferrer\"\u003Eステータス（英語）\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"],":type":"snowflake-site/components/container"},"container_copy_copy":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-d532d71426","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"text":{"id":"text-d7bb74ed8b","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003E業界\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/advertising-media-entertainment/\"\u003E広告・メディア・エンターテイメント\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/financial-services/\"\u003E金融サービス\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/healthcare-and-life-sciences/\"\u003Eヘルスケア・ライフサイエンス\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/manufacturing/\"\u003E製造\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/public-sector/\"\u003E 官公庁・公的機関\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/retail-consumer-goods/\"\u003E小売・消費財\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/solutions/industries/technology/\"\u003E テクノロジー\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"],":type":"snowflake-site/components/container"},"container_copy":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-7fca4c15fa","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"text":{"id":"text-c59e38a8aa","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003E企業情報\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/company/overview/about-snowflake/\"\u003ESnowflakeについて\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/leadership-and-board/\"\u003E\u003C/a\u003E\u003Ca href=\"https://careers.snowflake.com/us/en?_ga=2.189098923.1024280027.1746985324-1783381883.1746382047\"\u003E採用情報（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://investors.snowflake.com/overview/default.aspx\"\u003E投資家情報（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://trust.snowflake.com/\"\u003Eトラストセンター（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/brand-guidelines/\"\u003Eブランドガイドライン（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/contact/\"\u003Eお問い合わせ\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/news/\"\u003Eニュースルーム\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/esg/\"\u003EESG（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/snowflake-ventures/\"\u003ESnowflake Ventures（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/company/overview/end-data-disparity/\"\u003Eデータ格差の解消（英語）\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"],":type":"snowflake-site/components/container"},"container_copy_copy_":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-f72d61815a","appliedCssClassNames":"snowflake-responsive-container-inner-padding-small",":items":{"text":{"id":"text-ba6a63d240","additionalClasses":"sf-footer__link-group","text":"\u003Cp class=\"sf-footer__column-title\"\u003E学ぶ\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://snowflake.com/ja/resources/\"\u003Eリソースライブラリ\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/live-demo/?lang=ja\"\u003Eライブデモ\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/ja/fundamentals/\"\u003EAIデータクラウドの基礎 \u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/resources/learn/training/\"\u003Eトレーニング（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/resources/learn/certifications/\"\u003E認定資格\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://learn.snowflake.com/en/\" target=\"_blank\"\u003ESnowflake University（英語）\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://www.snowflake.com/ja/developers/guides/\" target=\"_self\"\u003E開発者ガイド\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca rel=\"noopener noreferrer\" href=\"https://docs.snowflake.com/ja\" target=\"_blank\"\u003Eドキュメント\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"/ja/data-governance/\"\u003Eデータガバナンス\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"],":type":"snowflake-site/components/container"}},":itemsOrder":["container_1622723482","container","container_copy_copy","container_copy","container_copy_copy_"],":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"],":type":"snowflake-site/components/container"},"container_573483281_":{"additionalClasses":"sf-footer__bottom","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container_112062425":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-c0aae8a583","appliedCssClassNames":"snowflake-responsive-container-inner-padding-none",":items":{"container_112062425":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"flexible_column_cont":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-7ab308a3bb","appliedCssClassNames":"snowflake-container snowflake-responsive-container-inner-padding-small",":items":{"flexible_column_cont":{"id":"flexible-column-container-dedb402fd7","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-11c8d82ef0",":items":{"container":{"additionalClasses":"sf-footer__legal-container","layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12","text_copy_copy_16360_1954079702":"aem-GridColumn aem-GridColumn--default--12","markup_editor":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-86aa034b00","appliedCssClassNames":"snowflake-responsive-container-inner-padding-none",":items":{"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"image":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-72135f8a75","appliedCssClassNames":"snowflake-responsive-container-inner-padding-extra-small",":items":{"image":{"id":"image-8d0fd8e062","additionalClasses":"sf-footer__logo","height":"64","alt":"Snowflake logo","imageLink":{"valid":true,"url":"/en/"},"isLcpImage":false,"lazyEnabled":true,"src":"https://www.snowflake.com/content/experience-fragments/snowflake-site/language-masters/ja/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","width":"64",":type":"snowflake-site/components/image"}},":itemsOrder":["image"],":type":"snowflake-site/components/container"},"text_copy_copy_16360_1954079702":{"id":"text-a6fd8caaf5","additionalClasses":"sf-footer__legal-links","text":"\u003Cul\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/legal/privacy/privacy-policy/\"\u003Eプライバシー通知\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/en/legal/snowflake-site-terms/\"\u003Eサイト利用規約\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://info.snowflake.com/Preference-center.html\"\u003Eメール配信設定\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Cbutton id=\"ot-sdk-btn\" class=\"ot-sdk-show-settings\"\u003Eクッキーの設定\u003C/button\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/legal/privacy/privacy-policy/#12\"\u003E個人情報を共有しない\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/legal/\"\u003E法務関連\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E© 2026 Snowflake Inc. All Rights Reserved\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-3110ea7c9b","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_Japan\" 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","cssUrl":"/content/experience-fragments/snowflake-site/language-masters/ja/site/footer/master/_jcr_content/root/container_573483281_/container_112062425/flexible_column_cont/flexible_column_content_container_1/container/markup_editor.a1b733f3995ad01d.css",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["container","text_copy_copy_16360_1954079702","markup_editor"],":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"],":type":"snowflake-site/components/container"}},":itemsOrder":["container_112062425"],":type":"snowflake-site/components/container"},"markup_editor_copy":{"id":"markup-editor-4d054a2d18","title":"New css","cssContent":".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}.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:1.4}.related-chip-25 .snowflake-content-chip-image{width:48px}.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:hover::after{right:24px;transition:300ms ease right}.related-chip-25 .snowflake-content-chip-content-without-tag{flex-grow:1;padding-right:24px}.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}.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}.language-ja .snowflake-title-v2.dynamic .heading-2-v2 span.snowflake-title-v2-line{font-size:clamp(2.5rem,3.5vw,4rem) !important;line-height:1.2 !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 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}",":type":"snowflake-site/components/markup-editor","isGSAPEnabled":false}},":itemsOrder":["container_copy_811922734","container_573483281_","markup_editor_copy"],":type":"snowflake-site/components/container"}},":itemsOrder":["root"],"classNames":"aem-xf",":type":"snowflake-site/components/experiencefragment"},"experiencefragment":{"id":"experiencefragment-7f92eeb8d9","configured":false,":items":{},":itemsOrder":[],"classNames":"aem-xf empty",":type":"snowflake-site/components/experiencefragment"}},":itemsOrder":["experiencefragment-banner","experiencefragment-header","markup_editor","responsivegrid","modal_container","experiencefragment-footer","experiencefragment"],":type":"wcm/foundation/components/responsivegrid"}},":itemsOrder":["root"],"coveoConfig":{"apiKey":"xx335921a6-2a0a-40f2-a167-e390b4766c3d","organizationId":"snowflakecomputingproduction8neljofn","searchHub":"snowflake.com","pipeline":"snowflake.com"},"analyticsDebugMode":false,"analyticsData":{"excludeFromAnalytics":false,"subCategory":"","pageType":"homepage","templateName":"fundamentals-template","siteName":"snowflake","pageUrl":"/content/snowflake-site/global/ja/artificial-intelligence/machine-learning/automl","language":"ja","category":"general","pageName":"AutoML（自動機械学習）とは：仕組みとユースケース、限界までを解説","contentTags":["snowflake-site:taxonomy/content-type/fundamentals","snowflake-site:taxonomy/product/ai"]},":mappedPath":"/ja/artificial-intelligence/machine-learning/automl/",":type":"snowflake-site/components/structure/page","locale":"ja"}