Microsoft Certified: Fabric Analytics Engineer AssociateImplement and manage semantic models (30-35%)Medium
A data engineer is configuring a semantic model in Microsoft Fabric. The model sources data from an Azure SQL Database. To improve query performance for frequently accessed aggregated data, the engineer wants to ensure that specific measures always leverage pre-calculated values. Which feature should the engineer implement to achieve this without requiring users to directly interact with aggregated tables?
- ASet up Object-Level Security (OLS).
- BCreate Calculation Groups.
- CImplement Row-Level Security (RLS).
- DDefine manual aggregation tables.
Show answer & explanationAnswer & explanation
Correct answer: D. Define manual aggregation tables.
Manual aggregation tables allow the data engineer to explicitly define and manage pre-calculated summary tables within the semantic model. The engine then intelligently redirects queries from the detail tables to these aggregations, significantly improving performance for aggregated queries without requiring user intervention.
Why the other options are wrong
- A. OLS is for securing access to tables or columns, not for improving query performance through pre-calculation.
- B. Calculation Groups are for simplifying the creation and management of common measure definitions, not for pre-calculating and storing aggregated data.
- C. RLS is for securing rows of data, not for performance optimization of aggregated queries.
Manual Aggregation Tables
Manual aggregation tables are pre-calculated summary tables created within a Microsoft Fabric semantic model to significantly improve query performance for aggregated data by redirecting queries from detailed tables.
- Engineers define aggregations explicitly.
- Queries are automatically rewritten to use aggregations.
- Reduces query time for large datasets.
Memory trick: Accelerate Queries: Aggregate, Cache, or Stream!