Data Monitoring / Power BI Performance & KPI Integrity
Power BI: Many-to-many relationship inflation
Revenue appears twice after combining two fact-like tables. Inspect relationship cardinality and compare distinct business keys at the intended grain.
Environment and inputs: Power BI semantic models and reports; measure behavior depends on relationships, storage mode and filter context.
Failure scenario
Revenue appears twice after combining two fact-like tables. Confirm the cause before choosing a fix.
Evidence to collect
Inspect relationship cardinality and compare distinct business keys at the intended grain. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Introduce a controlled bridge or conformed dimension and reconcile totals at each grain. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for many-to-many relationship inflation 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.