Slow dashboard querying a large fact table: first three checks?
This tests systematic diagnosis of fact-table query latency. A strong answer checks the execution plan and indexing, evaluates partitioning and data model fit, and inspects caching or pre-aggregation.
This tests whether you can methodically diagnose data warehouse latency from the dashboard layer down to storage. A strong response starts with the query execution plan and indexing on the fact table, moves to schema design and partitioning alignment with filter patterns, then evaluates caching, materialized views, or pre-aggregated rollups. It should also mention concurrency and queue wait times. A red flag is immediately suggesting cluster scaling before inspecting the query plan, table scans, and join logic.
Read the original → multishoring.com
- #data warehouse
- #query optimization
- #performance tuning
- #analytics engineering
- #bi dashboards
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