Refer to this topic for information on fixed issues and known limitations associated with Data Quality.
| Issue | Summary | Workaround | Noted on |
|---|---|---|---|
| Geolocation API source preview fails with “NullPointerException” | When you attempt to preview a transformation step that uses the Geolocation Address API source in a data quality pipeline, the preview operation fails. This limitation affects only the preview functionality in the transformation step editor. | None | December 2025 |
| Step preview row limit in Data Quality pipelines | The Step Preview feature supports a maximum of 500 rows in total, distributed across all input sources for an operator. For example, if a step has two input datasets, only 250 rows from each will be included in the preview. This may result in incomplete previews when working with larger datasets. | For Upload File sources used in sample generation, ensure that the most relevant records are positioned at the top of the file. | June 2025 |
| Agent selection impact | If no agent is selected, the Insights feature will be disabled due to the absence of agent selection. This means that in order to enable the Insights feature, an agent must be actively chosen. | None | November 2024 |
| Data-type limitation in quality rules | The 'Time' datatype is not supported when setting up Catalog rules for Dataproc or BigQuery connections. It defaults to 'String', which may affect rule accuracy. | Currently, there is no direct workaround. To ensure accurate rule evaluation when using Dataproc or BigQuery connections, consider using alternative data-types. | December 2024 |
| Quality score generation with profiling | When configuring a datasource with Profile Datasets toggle enabled and the Run Quality Rules and Calculate Scores toggle disabled it is noticed that a quality score is generated for certain datasets, providing additional insights beyond the expected behavior. | NA | March 2025 |
| Custom data quality rule evaluation with CSV files | When evaluating custom data quality rules using assets stored in CSV files within the Amazon S3 datasource, the process tends to take longer compared to working with other file formats such as Parquet or JSON. This delay occurs because, during the rule evaluation, all fields in the dataset are read from the CSV file, rather than selectively accessing only the required fields. | NA | February 2026 |