SourceAmazon SageMaker Unified Studio now supports data profiling and anomaly detection
Data professionals can identify data errors and drifts automatically, reducing the need to manually create and maintain complex validation rules.
- Powered by AWS Glue Data Quality to generate statistical profiles and track changes over time
- Provides on-demand and scheduled profiling on catalog tables via a dedicated Data profile tab
- Enables anomaly detection that builds baselines of expected behavior without predefined thresholds or custom rules
- Supports both data at rest in catalog tables and data in transit within Visual ETL jobs using Evaluate Data Quality transforms
- Available in all AWS Regions where Amazon SageMaker Unified Studio is supported