Microsoft Certified: Fabric Analytics Engineer AssociateImplement and manage semantic models (30-35%)Medium
A data engineer is optimizing a large semantic model in Microsoft Fabric. The model sources data from a Synapse Data Warehouse and contains several large fact tables. Users frequently run reports that aggregate data from these fact tables, but the queries are slow. The engineer notices that the same aggregations are repeatedly calculated. Which feature should the engineer implement to improve query performance by pre-calculating and storing these frequently used aggregations?
- AAutomatic Aggregations
- BRow-Level Security (RLS)
- CDirectQuery Mode
- DBidirectional Cross-Filter
Show answer & explanationAnswer & explanation
Correct answer: A. Automatic Aggregations
Automatic Aggregations in Microsoft Fabric (and Power BI) automatically create and manage aggregated tables for DirectQuery and Dual storage models. This feature intelligently detects frequently used queries and creates appropriate aggregations, significantly speeding up query performance by serving pre-calculated results.
Why the other options are wrong
- B. RLS is a security feature, not a performance optimization for query aggregation speed.
- C. DirectQuery mode itself can be slow for complex aggregations; it's a storage mode, not a performance optimization for repeated aggregations.
- D. Bidirectional cross-filter is for relationship behavior, not for pre-calculating and storing aggregated data.
Automatic Aggregations
Automatic Aggregations in Microsoft Fabric pre-calculate and store frequently queried data summaries to dramatically improve query performance, especially for DirectQuery models.
- Automates the creation and management of aggregation tables.
- Primarily benefits DirectQuery and Dual storage models.
- Reduces query time by serving pre-computed results.
Memory trick: Speed up facts, aggregate smart, let the engine play its best part.