Forum Discussion
Error while refreshing dataflow gen2
- 11 months ago
Hello Shubham_rai955,
✅ Why this happens
Even though you mentioned no transformations in M, the incremental refresh policy still applies filters and type conversions. If any column expected as Number contains a Text value (or vice versa), Power Query throws this error.
✅ How to fix it
Check column data types in the source
- Ensure that the column used for incremental refresh (usually a date or numeric key) and any numeric columns are consistently typed.
- If the source has mixed types (e.g., numbers stored as text), clean them before refresh.
Add explicit type conversion in Power Query
- In the Dataflow Gen2 editor, select the problematic column → set Data Type to Text or Number explicitly.
- Or use try ... otherwise in M to handle invalid values
Validate incremental refresh filters
- If the policy applies on a column that isn’t strictly numeric or date, adjust it.
Preview the query in the editor
- Check for rows with unexpected values (e.g., text in numeric columns).
You can also Re-run a full refresh once
Disable incremental refresh temporarily.
Run a full refresh to confirm if the issue is only with incremental partitions.
If full refresh succeeds, re-enable incremental refresh.
Hope it can help you !
Best regards,
Antoine
Hello Shubham_rai955,
✅ Why this happens
Even though you mentioned no transformations in M, the incremental refresh policy still applies filters and type conversions. If any column expected as Number contains a Text value (or vice versa), Power Query throws this error.
✅ How to fix it
Check column data types in the source
- Ensure that the column used for incremental refresh (usually a date or numeric key) and any numeric columns are consistently typed.
- If the source has mixed types (e.g., numbers stored as text), clean them before refresh.
Add explicit type conversion in Power Query
- In the Dataflow Gen2 editor, select the problematic column → set Data Type to Text or Number explicitly.
- Or use try ... otherwise in M to handle invalid values
Validate incremental refresh filters
- If the policy applies on a column that isn’t strictly numeric or date, adjust it.
Preview the query in the editor
- Check for rows with unexpected values (e.g., text in numeric columns).
You can also Re-run a full refresh once
Disable incremental refresh temporarily.
Run a full refresh to confirm if the issue is only with incremental partitions.
If full refresh succeeds, re-enable incremental refresh.
Hope it can help you !
Best regards,
Antoine