What causes UserErrorSchemaNotMatch?

Source column data type changed (e.g., INT widened to BIGINT or VARCHAR shortened) without updating the sink schema. A required column exists in the sink but is absent or renamed in the source. Auto-mapping is enabled but column names differ between source and sink. Schema drift in the source (e.g., CSV header row removed or reordered). Explicit column mapping in the copy activity is stale after a source schema change

How do I fix UserErrorSchemaNotMatch?

Open the copy activity in ADF and click 'Import schemas' for both source and sink to refresh the detected schema.. Compare source and sink column lists side-by-side — identify the mismatched or missing column.. Update the explicit column mapping in the copy activity to reflect the current schemas.. If the sink schema must stay fixed, add a derived column transformation upstream to cast the source column to the expected type.. Enable schema drift tolerance in data flows if the source schema changes frequently and the sink can accommodate it.. Check for recent DDL changes on the source table or file format changes on the source storage.

High severityconfiguration

Power BI Refresh Error:
UserErrorSchemaNotMatch

What does this error mean?

ADF found that the source and sink schemas are incompatible. A column type, name, or structure in the source does not match what the sink expects and cannot be resolved automatically.

Common causes

1Source column data type changed (e.g., INT widened to BIGINT or VARCHAR shortened) without updating the sink schema
2A required column exists in the sink but is absent or renamed in the source
3Auto-mapping is enabled but column names differ between source and sink
4Schema drift in the source (e.g., CSV header row removed or reordered)
5Explicit column mapping in the copy activity is stale after a source schema change

How to fix it

1Open the copy activity in ADF and click 'Import schemas' for both source and sink to refresh the detected schema.
2Compare source and sink column lists side-by-side — identify the mismatched or missing column.
3Update the explicit column mapping in the copy activity to reflect the current schemas.
4If the sink schema must stay fixed, add a derived column transformation upstream to cast the source column to the expected type.
5Enable schema drift tolerance in data flows if the source schema changes frequently and the sink can accommodate it.
6Check for recent DDL changes on the source table or file format changes on the source storage.

Frequently asked questions

Can I make the copy activity ignore schema differences?

For file-based sinks enable schema drift, but for structured sinks like SQL or Synapse the sink schema is enforced. The safest fix is to keep the explicit mapping current.

Will the copy activity retry automatically?

ADF retries transient errors, but schema mismatches are permanent configuration errors. They will fail on every retry until the mapping is corrected.

Official documentation: azure-data-factory