Data Monitoring / Power BI Refresh & Data Reliability
Power BI: DirectQuery freshness assumptions
A team expects every visual to reflect an immediately committed transaction. Compare the semantic model storage mode, query timing and any report or source caching behavior.
Environment and inputs: Power BI Desktop and Power BI service; gateway, connector, capacity and license capabilities depend on the deployed configuration.
Failure scenario
A team expects every visual to reflect an immediately committed transaction. Confirm the cause before choosing a fix.
Evidence to collect
Compare the semantic model storage mode, query timing and any report or source caching behavior. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Document the actual freshness path and measure end-to-end lag rather than promising instantaneous updates. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for directquery freshness assumptions using the same scope and a representative interval. Check that the symptom is resolved, expected records are present and downstream results are correct. If coverage, correctness or latency worsens, restore the recorded configuration through the agreed rollback process.
Scope and precautions
Prefer read-only access and limit queries to the relevant period or dataset. This example has not been tested on your systems. Test changes in an approved environment. Keep credentials and sensitive data out of shared evidence.