What causes DF-Executor-InvalidType?

A column is mapped to a sink column of an incompatible type without an explicit cast — for example, a string column mapped to an integer sink column. An expression function receives a column of the wrong type — e.g., a string column in an arithmetic expression or a date column in a string function. The source schema type for a column changed (e.g., from integer to string) and downstream expressions still treat it as an integer. A parameter passed to the data flow has a different type than declared in the data flow parameter definition

How do I fix DF-Executor-InvalidType?

Check the ADF activity run output for the column name and type mismatch detail — the error names the column and the conflicting types.. Add a Derived Column transformation before the sink to explicitly cast the column to the expected type: use `toInteger()`, `toDecimal()`, `toString()`, or `toDate()` as appropriate.. If the source sends mixed types in the same column (e.g., integers and strings), add a conditional expression: `iif(isString(col), toInteger(col), col)`.. In the sink Mapping tab, verify the source column type is compatible with the target column type and adjust the sink schema if needed.. Enable debug mode to preview the column at the point of failure and confirm the actual data types being processed.

Medium severitydata flow

Power BI Refresh Error:
DF-Executor-InvalidType

What does this error mean?

A data type mismatch occurred in the data flow — a column or expression is being used as a type it is not.

Common causes

1A column is mapped to a sink column of an incompatible type without an explicit cast — for example, a string column mapped to an integer sink column
2An expression function receives a column of the wrong type — e.g., a string column in an arithmetic expression or a date column in a string function
3The source schema type for a column changed (e.g., from integer to string) and downstream expressions still treat it as an integer
4A parameter passed to the data flow has a different type than declared in the data flow parameter definition

How to fix it

1Check the ADF activity run output for the column name and type mismatch detail — the error names the column and the conflicting types.
2Add a Derived Column transformation before the sink to explicitly cast the column to the expected type: use `toInteger()`, `toDecimal()`, `toString()`, or `toDate()` as appropriate.
3If the source sends mixed types in the same column (e.g., integers and strings), add a conditional expression: `iif(isString(col), toInteger(col), col)`.
4In the sink Mapping tab, verify the source column type is compatible with the target column type and adjust the sink schema if needed.
5Enable debug mode to preview the column at the point of failure and confirm the actual data types being processed.

Frequently asked questions

How is InvalidType different from the Conversion error?

InvalidType is a structural mismatch — a value is passed to a context requiring a different type; it fails pre-execution. Conversion is a runtime error where the type is correct but the value can't be cast (e.g., 'N/A' to integer).

How do I check column types in the data flow to find the mismatch?

Hover over a column in Data Preview or the Projection tab to see its type. In the sink Mapping tab, source and target types appear side by side — mismatches are visible. Use 'Import projection' on the source.

Can I add an explicit cast to fix InvalidType without changing the sink schema?

Yes — add a Derived Column before the sink and cast explicitly: toInteger(columnName), toString(columnName), toDate(columnName, 'yyyy-MM-dd'), etc. This converts the value before it reaches the sink mapping.

Will downstream Power BI datasets be affected?

Yes — the pipeline fails and no data reaches the target. Dependent datasets serve stale figures.

Official documentation: https://learn.microsoft.com/en-us/azure/data-factory/data-flow-troubleshoot-guide