Tuning a Fabric warehouse for faster queries

Optimizing a Fabric data warehouse focuses on ensuring queries use efficient distribution and statistics, minimizing data movement, and using appropriate table structures and V-Order optimization. Monitoring tools like Query Insights, Dynamic Management Views (DMVs), and the Fabric Capacity Metrics app help identify bottlenecks such as long-running queries, resource contention, or skewed data distribution.

Must-know

• Fabric Warehouse automatically manages statistics, but you can manually update them using CREATE STATISTICS or UPDATE STATISTICS when auto-generated stats are stale or insufficient for complex queries.
• The queryinsights schema (exec_requests_history, exec_sessions_history, frequently_run_queries) provides historical query performance data useful for identifying slow or resource-intensive queries.
• V-Order is a write-time optimization applied to Parquet files in Fabric that improves compression and read performance for Power BI and SQL engines, and is enabled by default for Warehouse tables.
• Minimizing data movement is critical: use appropriate JOIN strategies and avoid unnecessary CROSS JOINs or SELECT * on large fact tables to reduce compute and I/O overhead.
• Result set caching can improve performance for repeated identical queries, but is invalidated whenever underlying table data changes, so it's most effective for stable reporting workloads.
• DMVs like sys.dm_exec_requests and sys.dm_pdw_exec_requests (in the Warehouse SQL endpoint) let you monitor active queries in real time to detect blocking, long-running operations, or excessive resource consumption.

Coverage checked against the published exam guide on Aug 12, 2026.

These are independent practice questions, written against this certification's published exam guide. They are not the certification vendor's own questions, and not the real exam.