Data Monitoring / Power BI Performance & KPI Integrity
Power BI: Model grain mismatch
Daily facts are joined to monthly targets and target totals multiply. Inspect the date grain of each table and calculate targets at their native month grain.
Environment and inputs: Power BI semantic models and reports; measure behavior depends on relationships, storage mode and filter context.
Failure scenario
Daily facts are joined to monthly targets and target totals multiply. Confirm the cause before choosing a fix.
Evidence to collect
Inspect the date grain of each table and calculate targets at their native month grain. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Use a model and measure that respect both grains and reconcile a month with several daily rows. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for model grain mismatch 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.