BigQuery Data Quality Studio Private Preview

Overview: Monitor the quality of your BigQuery assets in Atlan using BigQuery's native capabilities. This integration lets you create rules, track metrics, and view data quality insights directly within Atlan's discovery, lineage, and data products.

Get started

Follow these steps to set up BigQuery as your data quality studio:

• Set up BigQuery
• Enable data quality on a connection

Known limitations

• Single region support: BigQuery DQS currently supports a single region only. The DQS dataset must be created in the same location as the tables you want to monitor. All tables governed by DQS must be in the same region.
• Columns inside array of struct not supported: Data Quality Studio doesn't support columns that are nested inside an array of struct (ARRAY<STRUCT<...>>). You can't create data quality rules for these nested struct fields. For example, if you have a column defined as orders ARRAY<STRUCT<order_id INT64, amount FLOAT64>>, you can't create rules for the order_id or amount fields within the array.

References

• Rule types and failed rows validations: Reference guide for all available rule types and how failed rows validation works
• Compute and cost tracking: How DQS uses compute resources, how to track spend, and how to optimize costs