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04-13-2026 06:41 AM
Hi @IM_01,
Yes. Metric views are explicitly designed to give you SQL cube-like behaviour.
A metric view lets you define measures once, independent of dimensions, then aggregate those measures over any combination of dimensions at query time, which is the core behaviour you get from cubes.
When querying a metric view, you can use GROUP BY GROUPING SETS (and thus CUBE/ROLLUP patterns) on its dimensions, so you can generate detail rows, subtotals, and grand totals in a single query, just like with GROUP BY CUBE.
The main difference vs. a classic OLAP cube is that metric views are SQL/UC-native and compute aggregations on demand (optionally with materialization for performance), rather than maintaining a separate multidimensional cube engine.
If this answer resolves your question, could you mark it as “Accept as Solution”? That helps other users quickly find the correct fix.
Ashwin | Delivery Solution Architect @ Databricks
Helping you build and scale the Data Intelligence Platform.
***Opinions are my own***