What causes INCOMPATIBLE_DATA_FOR_TABLE?

Writing nullable values to a NOT NULL column without a DEFAULT or COALESCE expression. Writing additional struct fields to a table that was created without allowColumnDefaults or schema evolution enabled. A CHECK constraint on the table was violated by a new range of values in the source data. An INSERT INTO statement omits required columns, leaving them NULL when NOT NULL is enforced. Schema evolution was not enabled but the incoming DataFrame has extra columns compared to the table

How do I fix INCOMPATIBLE_DATA_FOR_TABLE?

Inspect the error message for the specific sub-cause: NULL in NOT NULL column, extra struct fields, or CHECK constraint violation.. For NULL issues, add COALESCE(col, default_value) upstream or set a DEFAULT in the table DDL.. For extra columns, enable schema evolution: .option('mergeSchema', 'true') on the write, or ALTER TABLE SET TBLPROPERTIES (delta.columnMapping.mode = 'name').. For CHECK constraint violations, review the constraint logic with SHOW TBLPROPERTIES on the table and fix the upstream data.. Use Delta Live Tables expectations to catch violations earlier in the pipeline.

High severitydata quality

Power BI Refresh Error:
INCOMPATIBLE_DATA_FOR_TABLE

What does this error mean?

Data being written to a Delta table is incompatible with the table's schema or constraints. This includes writing nullable values to a NOT NULL column, writing extra columns to a struct with no extra-field support, or writing values that violate a CHECK constraint.

Common causes

1Writing nullable values to a NOT NULL column without a DEFAULT or COALESCE expression
2Writing additional struct fields to a table that was created without allowColumnDefaults or schema evolution enabled
3A CHECK constraint on the table was violated by a new range of values in the source data
4An INSERT INTO statement omits required columns, leaving them NULL when NOT NULL is enforced
5Schema evolution was not enabled but the incoming DataFrame has extra columns compared to the table

How to fix it

1Inspect the error message for the specific sub-cause: NULL in NOT NULL column, extra struct fields, or CHECK constraint violation.
2For NULL issues, add COALESCE(col, default_value) upstream or set a DEFAULT in the table DDL.
3For extra columns, enable schema evolution: .option('mergeSchema', 'true') on the write, or ALTER TABLE SET TBLPROPERTIES (delta.columnMapping.mode = 'name').
4For CHECK constraint violations, review the constraint logic with SHOW TBLPROPERTIES on the table and fix the upstream data.
5Use Delta Live Tables expectations to catch violations earlier in the pipeline.

Frequently asked questions

How do I enable schema evolution for Delta writes in PySpark?

Add .option('mergeSchema', 'true') to your DataFrame writer: df.write.format('delta').option('mergeSchema', 'true').mode('append').save(path).

Can I temporarily disable CHECK constraints to unblock a pipeline?

Yes — ALTER TABLE t DROP CONSTRAINT constraint_name removes it. Re-add after fixing the data, or use a weaker WARN mode constraint in Delta Live Tables.