{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/e25f23ff562f4604a4408b2c64aa416d\" frameborder=\"0\" width=\"1916\" height=\"1437\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1437,"width":1916,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1437,"thumbnail_width":1916,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/e25f23ff562f4604a4408b2c64aa416d-1291f0912d637110.gif","duration":445.121,"title":"Semantic Layer on top of Snowflake with Cube, KPI Governance, Self-Service Analytics, Single Source of Truth","description":"This Loom demonstrates a semantic layer with Cube on top of a Snowflake data warehouse. It shows how Cube uses YAML to define joins across cubes for products, users, orders, and dates, so BI tools only see the contract and not the underlying remodeling. In self-service mode, analysts drag and drop measures like Net Revenue and Gross Margin Rate and select a year field, without writing SQL, while Cube generates the semantic SQL and the real Snowflake SQL. The video also illustrates filtering out returned products by status and concludes that the semantic layer centralizes KPI and metric computation for consistent governance across all consumers."}