Aggregations in Power BI
summary
Shows how Power BI rewrites slow DirectQuery SQL into smaller pre-aggregated tables and when that succeeds or fails, using DAX Studio performance traces and Power BI Performance Analyzer to see “match found” rewrites. Builds sales_by_date and sales_by_customer_date in SQL (recommended as a materialized view in SQL Server), sets aggregation mappings and precedence, and converts row-level pricequantity into a calculated column for line amount* so SUM can match. Some queries rewrite and run in-memory fast; others fail when required dimensions (product brand) aren’t in the aggregation or when imported aggregates become stale.
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chapters (9)
- 0:00Aggregations in Power BI
- 4:07Power BI engine architecture
- 12:59Manual aggregations in DirectQuery
- 28:48Complex measures with aggregations
- 34:40Aggregation types
- 38:56Switching to Import mode
- 45:26When to use aggregations
- 49:00Automatic aggregations limits
- 50:25Conclusion
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