What causes WildcardPathSinkNotSupported?

Wildcard path not supported for sink. Integration runtime configuration is incorrect or outdated. Authentication credentials or permissions are insufficient. The feature or setting is not supported for the selected connector or copy mode

How do I fix WildcardPathSinkNotSupported?

Open the copy activity's sink dataset and remove the wildcard character (* or ?) from the file path — sink paths must be a fixed, fully specified path where ADF can write the output file.. If the intention was to write to a dynamically named file, use an ADF expression instead of a wildcard — for example, set the file name to @concat('output_', formatDateTime(utcNow(), 'yyyyMMdd'), '.csv') in the sink dataset settings.. If you need to read from multiple files (wildcard source) and write to a single output, that is the correct configuration — wildcards are valid in the source, not the sink.. Check whether the path was copied from a source dataset configuration — source wildcard paths cannot be reused directly as sink paths.. After fixing the sink path, validate the pipeline using the 'Validate' button in ADF Studio before running.

Medium severityconfiguration

Power BI Refresh Error:
WildcardPathSinkNotSupported

What does this error mean?

The sink configuration uses a wildcard path pattern, which is not supported when writing data. Wildcard patterns are only valid for source datasets, not sink datasets.

Common causes

1Wildcard path not supported for sink
2Integration runtime configuration is incorrect or outdated
3Authentication credentials or permissions are insufficient
4The feature or setting is not supported for the selected connector or copy mode

How to fix it

1Open the copy activity's sink dataset and remove the wildcard character (* or ?) from the file path — sink paths must be a fixed, fully specified path where ADF can write the output file.
2If the intention was to write to a dynamically named file, use an ADF expression instead of a wildcard — for example, set the file name to @concat('output_', formatDateTime(utcNow(), 'yyyyMMdd'), '.csv') in the sink dataset settings.
3If you need to read from multiple files (wildcard source) and write to a single output, that is the correct configuration — wildcards are valid in the source, not the sink.
4Check whether the path was copied from a source dataset configuration — source wildcard paths cannot be reused directly as sink paths.
5After fixing the sink path, validate the pipeline using the 'Validate' button in ADF Studio before running.

Frequently asked questions

Does this configuration error affect every pipeline run?

Yes — configuration errors are deterministic. Every run fails until fixed; retrying does not help.

How do I validate an ADF pipeline configuration before running it?

Click 'Validate' in the ADF authoring UI for configuration checks. For data flows, use Debug mode with a small sample to validate expressions and mappings.

Can dynamic content expressions in ADF cause configuration errors at runtime?

Yes — @activity(), @pipeline(), or @dataset() parameters that resolve to null or an unexpected type cause runtime failures even when design-time validation passes.

Do configuration errors appear in the ADF activity output?

Yes — the ADF Monitor activity detail shows the error code and the specific property that is invalid or missing.

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