Monitor data quality in data processing jobs

When a Visual ETL job includes an Evaluate Data Quality transform, the data quality results are captured and displayed on the data processing jobs page. This gives you a centralized view of quality checks that ran as part of your data integration pipeline.

Rules are written using DQDL (Data Quality Definition Language), a domain-specific language for defining data quality rules, with 31 built-in rule types. For details on configuring the Evaluate Data Quality transform, defining rules, and selecting outputs, see Evaluate data quality transform. For the full list of rule types and syntax, see DQDL rule types in the AWS Glue documentation.