Data Monitoring / Power BI Refresh & Data Reliability
Power BI: Data type conversion failures
Only a subset of date or amount values fails a transformation. Inspect rejected values and locale assumptions instead of treating every null as absent source data.
Environment and inputs: Power BI Desktop and Power BI service; gateway, connector, capacity and license capabilities depend on the deployed configuration.
Failure scenario
Only a subset of date or amount values fails a transformation. Confirm the cause before choosing a fix.
Evidence to collect
Inspect rejected values and locale assumptions instead of treating every null as absent source data. Record the time, affected scope and a healthy comparison interval.
Fix the confirmed cause
Specify the intended locale and route invalid records to an observable rejection path. Write the expected result first. Change one relevant setting at a time.
Check the result and hand over
Repeat the check for data type conversion failures 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.