Amazon SageMaker Unified Studio now supports data quality rule authoring and evaluation
News
This article announces data quality rule authoring and evaluation capabilities in Amazon SageMaker Unified Studio, powered by AWS Glue Data Quality.
- Define and evaluate data quality rules directly within SageMaker Unified Studio
- Supports both data at rest in catalog tables and data in transit in Visual ETL jobs
- Uses Data Quality Definition Language (DQDL) for rule authoring
- Dedicated Data Quality tab enables on-demand or scheduled evaluations
- Checks completeness, uniqueness, freshness, accuracy, and other dimensions
- Available in all AWS Regions where SageMaker Unified Studio is available
This feature helps data teams catch quality issues before bad data impacts data lakes and downstream analytics or ML workloads.
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