SageMaker Unified Studio adds data quality rule authoring and evaluation
Amazon SageMaker Unified Studio now supports authoring and evaluating data quality rules, leveraging AWS Glue Data Quality. This integration allows data professionals to define rules, assess data quality in catalog tables and ETL jobs, and identify issues early to prevent bad data from impacting downstream workflows. The feature is available in all SageMaker Unified Studio regions for both IAM Identity Center and IAM-based domains.
- →Data quality rule authoring and evaluation in SageMaker Unified Studio
- →Two workflows for data quality evaluation
- →Broad rule definition capabilities
- →Availability
Features (1) ›
- Data quality rule authoring and evaluation in SageMaker Unified Studio
Amazon SageMaker Unified Studio now allows users to author and evaluate data quality rules, integrating with AWS Glue Data Quality. This enables data engineers, analysts, and scientists to define rules, run evaluations on data at rest or in transit, and view results within the studio environment.
Enhancements (2) ›
- Two workflows for data quality evaluation
Users can evaluate data quality through two distinct workflows: a dedicated Data Quality tab for catalog assets (data at rest) and an Evaluate Data Quality transform for Visual ETL jobs (data in transit). Both workflows support authoring rules using the Data Quality Definition Language (DQDL) and provide detailed evaluation results.
- Broad rule definition capabilities
The new feature allows the creation of rulesets capable of checking various data quality dimensions, including completeness, uniqueness, freshness, and accuracy. These rules help ensure data integrity before it is used in analytics or machine learning.
Notes (1) ›
- Availability
This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is offered. It supports both AWS IAM Identity Center-based and IAM-based domains, ensuring broad accessibility for users.
https://aws.amazon.com/about-aws/whats-new/2026/05/smus-data-quality
Related releases
- SageMaker Unified Studio Enhances Git Version Control Across Project Tools AWS What's New ·
- AWS Glue Data Quality Adds Distribution Statistics for Data Profiling AWS What's New ·
- SageMaker Inference Adds NVIDIA G7 Instances for Faster LLM Deployment AWS What's New ·
- Amazon SageMaker AI inference adds G6 instances in AWS GovCloud AWS What's New ·
- Amazon SageMaker G7e instances expand to Seoul, London, and Tokyo AWS What's New ·
- SageMaker Studio Integrates with Amazon OpenSearch for Unified Data Analysis AWS What's New ·