Microsoft Certified: Fabric Analytics Engineer AssociateImplement and manage semantic models (30-35%)Medium
A data architect is designing a semantic model in Microsoft Fabric. The model will contain a large fact table and several dimension tables. To optimize query performance, especially for common aggregations (e.g., total sales by region, average order value by date), the architect wants to pre-calculate and store these results within the semantic model itself, while still allowing drill-through to the detailed data. Which feature should the architect implement?
- AAutomatic Aggregations
- BIncremental Refresh
- CCalculated Tables
- DDirectQuery Partitions
Show answer & explanationAnswer & explanation
Correct answer: A. Automatic Aggregations
Automatic Aggregations allow the semantic model to automatically create and manage aggregated tables, which are used to answer queries faster, while still providing access to the detailed data when needed.
Why the other options are wrong
- B. Incremental refresh manages the refresh process for large datasets, but does not create or manage aggregate tables for query optimization.
- C. Calculated tables are static tables defined by DAX expressions and do not dynamically optimize queries against a fact table.
- D. DirectQuery partitions are used for managing data in DirectQuery mode, not for pre-calculating and storing aggregations.
Automatic Aggregations
A performance optimization feature in Microsoft Fabric semantic models that automatically creates and manages in-memory aggregate tables to speed up queries, while seamlessly redirecting queries between aggregates and detail data.
- Improves query performance for common aggregations.
- Automatically managed by the Fabric service.
- Allows drill-through to detailed data.
Memory trick: Aggregates are automatic, speed is magnetic.