{"id":5080,"date":"2026-02-24T11:59:45","date_gmt":"2026-02-24T11:59:45","guid":{"rendered":"https:\/\/www.arivonix.ai\/techsupport\/docs\/sql-clean-room-overview\/"},"modified":"2026-04-10T05:41:59","modified_gmt":"2026-04-10T05:41:59","password":"","slug":"sql-clean-room-overview","status":"publish","type":"docs","link":"https:\/\/www.arivonix.ai\/documentation\/docs\/sql-clean-room-overview\/","title":{"rendered":"SQL Cleanroom Overview"},"content":{"rendered":"<section class=\"documentation-content\">\n<h2>SQL Cleanroom<\/h2>\n<p>Execute SQL queries and analyze governed data in a secure, controlled environment while maintaining compliance and data governance.<\/p>\n<h2>Overview<\/h2>\n<p>The <strong>SQL Clean Room<\/strong> workspace provides a comprehensive environment for working with approved datasets through SQL queries. Users can perform structured data analysis, prepare reports, and explore enterprise datasets in a secure and auditable manner.<\/p>\n<h2>Key Features<\/h2>\n<ul>\n<li><strong>Database Schema Selection<\/strong>: Located at the top of the screen, users can select their target database schema for analysis.<\/li>\n<li><strong>Central Query Editor<\/strong>: A dedicated space for writing and executing SQL queries.<\/li>\n<li><strong>Multiple Worksheets<\/strong>: Create and organize different analyses in separate worksheets.<\/li>\n<li><strong>Query Management<\/strong>: Save queries for future reference and reuse.<\/li>\n<li><strong>Query History<\/strong>: Review previously executed queries, monitor execution status, and access past results.<\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>SQL Cleanroom Execute SQL queries and analyze governed data in a secure, controlled environment while maintaining compliance and data governance. Overview The SQL Clean Room workspace provides a comprehensive environment for working with approved datasets through SQL queries. Users can perform structured data analysis, prepare reports, and explore enterprise datasets in a secure and auditable [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"doc_category":[175],"doc_tag":[],"class_list":["post-5080","docs","type-docs","status-publish","hentry","doc_category-sql-clean-room"],"year_month":"2026-04","word_count":121,"total_views":0,"reactions":{"happy":0,"normal":0,"sad":0},"author_info":{"name":"Hari","author_nicename":"hari","author_url":""},"doc_category_info":[{"term_name":"Sql Clean Room","term_url":"https:\/\/www.arivonix.ai\/documentation\/docs-category\/sql-clean-room\/"}],"doc_tag_info":[],"_links":{"self":[{"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/docs\/5080","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/docs"}],"about":[{"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/types\/docs"}],"author":[{"embeddable":true,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/comments?post=5080"}],"version-history":[{"count":2,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/docs\/5080\/revisions"}],"predecessor-version":[{"id":5384,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/docs\/5080\/revisions\/5384"}],"wp:attachment":[{"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/media?parent=5080"}],"wp:term":[{"taxonomy":"doc_category","embeddable":true,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/doc_category?post=5080"},{"taxonomy":"doc_tag","embeddable":true,"href":"https:\/\/www.arivonix.ai\/documentation\/wp-json\/wp\/v2\/doc_tag?post=5080"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}