{"canonicalLink":"https://www.snowflake.com/en/blog/authors/si-peng/","robotsTags":["index","follow"],"templateName":"blog-author-page","cssClassNames":"blog-author-page page basicpage summit-page","allowedRenditionsWidth":["320","480","640","768","960","1200","1440","1920"],"description":"Si Peng is a Staff Data Scientist.","language":"en","title":"Si Peng","analyticsPageType":"homepage","analyticsCategory":"general","analyticsSubCategory":"","excludeFromAnalytics":false,":mappedPath":"/en/blog/authors/si-peng/",":type":"snowflake-site/components/structure/page",":items":{"root":{"columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"experiencefragment-banner":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-sub-header":"aem-GridColumn aem-GridColumn--default--12","experiencefragment-pre-footer":"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"},":items":{"experiencefragment-banner":{"id":"experiencefragment-af47470485","configured":false,":type":"snowflake-site/components/experiencefragment"},"experiencefragment-header":{"id":"experiencefragment-1d5b03cbe2","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master/jcr:content","configured":true,":type":"snowflake-site/components/experiencefragment","xfModelPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/mega-nav-header/master.xfmodel.json","languageNavPath":"/content/snowflake-site/global/en/blog/authors/si-peng.languagenav.json","appliedCssClassNames":"snowflake-sticky-nav-host"},"experiencefragment-sub-header":{"id":"experiencefragment-3cbbb46064","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/sub-navigation/blog-sub-nav-no-progress-bar/jcr:content","configured":true,":type":"snowflake-site/components/experiencefragment","xfModelPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/sub-navigation/blog-sub-nav-no-progress-bar.xfmodel.json"},"responsivegrid":{"columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"container":"aem-GridColumn aem-GridColumn--default--12"},":items":{"container":{"layout":"RESPONSIVE_GRID","columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"blog_author_hero":"aem-GridColumn aem-GridColumn--default--12","author_more_post":"aem-GridColumn aem-GridColumn--default--12","blog_breadcrumb":"aem-GridColumn aem-GridColumn--default--12"},"id":"container-8ecd4dbb88",":type":"snowflake-site/components/container",":items":{"blog_breadcrumb":{"id":"breadcrumb-7c06d21359","breadcrumbItems":[{"title":"Blog","path":"/en/blog/","active":false},{"title":"Si Peng","path":"/en/blog/authors/si-peng/","active":false}],":type":"snowflake-site/components/blog/breadcrumb"},"blog_author_hero":{"id":"blog-author-hero-4e403b717a","authorName":{"lines":["Si Peng"],"type":"heading2",":type":"snowflake-site/components/title-v2"},"authorTitle":"Staff Data Scientist","authorBio":{"text":"Si Peng is a Staff Data Scientist.","richText":false,":type":"snowflake-site/components/text"},":type":"snowflake-site/components/blog/blog-author-hero"},"author_more_post":{"id":"author-more-post-bfc270d0f5",":type":"snowflake-site/components/blog/author-more-post","initialHits":{"hits":[{"configurationStatus":{"configured":true,"message":""},"tags":[{"tagText":"Data Engineering","tagColor":"#29B5E8"}],":type":"snowflake-site/components/blog/card","title":{"lines":["Is Your Data AI-Ready? Introducing the AI Readiness Score"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-c92bc6dc73","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/engineering/ai-readiness-score-data-framework0/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Is Your Data AI-Ready? Introducing the AI Readiness Score"},"publicationDate":"JUL 31, 2026","authors":[{"authorCta":{"id":"button-7f14f15a2d","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/si-peng/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Si Peng"}},{"authorCta":{"id":"button-3316974bd3","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/derenik-haghverdian/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Derenik Haghverdian"}}]}],"totalMatches":1},"searchConfig":{"sortOrderOptions":["desc","asc"],"defaultSortOrder":"desc","orderByOptions":["alphabetical","customPublicationDate"],"defaultOrderBy":"customPublicationDate","filterTagGroups":[{"title":"Countries","filterTags":[{"tagId":"snowflake-site:taxonomy/blog/countries-regions/country/france","filterTag":"blog/countries-regions/country/france","localizedTagTitle":"France"}]},{"title":"Regions","filterTags":[{"tagId":"snowflake-site:taxonomy/blog/countries-regions/region/apac","filterTag":"blog/countries-regions/region/apac","localizedTagTitle":"APAC"}]}],"pageSize":9,"searchApiPath":"https://publish-p57963-e462109.adobeaemcloud.com/conf/snowflake-site/settings/wcm/templates/blog-author-page/structure/_jcr_content/root/responsivegrid/container/author_more_post.filter.json?pagePath=/content/snowflake-site/global/en/blog/authors/si-peng","searchBarPlaceholderText":"Search articles","showSearchBar":true,"showFilterTags":false,"showPaginationControls":true},"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium"}},":itemsOrder":["blog_breadcrumb","blog_author_hero","author_more_post"],"appliedCssClassNames":"snowflake-container"}},":itemsOrder":["container"],":type":"wcm/foundation/components/responsivegrid"},"experiencefragment-pre-footer":{"id":"experiencefragment-973839a506","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/get-started-pre-footer/get-started-pre-footer/jcr:content","configured":true,":type":"snowflake-site/components/experiencefragment","xfModelPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/get-started-pre-footer/get-started-pre-footer.xfmodel.json"},"experiencefragment-footer":{"id":"experiencefragment-27de888321","localizedFragmentVariationPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/footer/master/jcr:content","configured":true,":type":"snowflake-site/components/experiencefragment","xfModelPath":"/content/experience-fragments/snowflake-site/language-masters/en/site/footer/master.xfmodel.json"}},":itemsOrder":["experiencefragment-banner","experiencefragment-header","experiencefragment-sub-header","responsivegrid","experiencefragment-pre-footer","experiencefragment-footer"],":type":"wcm/foundation/components/responsivegrid"}},":itemsOrder":["root"],":hierarchyType":"page",":path":"/content/snowflake-site/global/en/blog/authors/si-peng","isPasswordProtected":false,"analyticsContentTags":[],"analyticsEnabled":true,"coveoConfig":{"apiKey":"xx335921a6-2a0a-40f2-a167-e390b4766c3d","organizationId":"snowflakecomputingproduction8neljofn","searchHub":"snowflake.com","pipeline":"snowflake.com"},"analyticsDebugMode":false,"analyticsData":{"excludeFromAnalytics":false,"subCategory":"","pageType":"homepage","templateName":"blog-author-page","siteName":"snowflake","pageUrl":"/content/snowflake-site/global/en/blog/authors/si-peng","language":"en","category":"general","pageName":"Si Peng","contentTags":[]},"locale":"en"}