AWS Glue announces GA of new ML-powered Glue Data Quality capability

AWS Glue announces the general availability of a new ML-powered Glue Data Quality capability that uses anomaly detection algorithms to identify hard-to-find data quality issues and anomalies, helping customers proactively identify and fix data quality issues.

Specifically, the article covers:

• Glue Data Quality (Glue DQ) now has an Anomaly Detection capability that uses ML algorithms to detect unexpected data quality issues.
• Customers can write rules or analyzers and turn on Anomaly Detection in Glue ETL to collect statistics, apply ML algorithms, and generate visual observations explaining detected issues.
• Recommended rules can be used to capture anomalous patterns, and customers can provide feedback to tune the ML model.
• This capability is available in several AWS regions, including US East (N. Virginia), Europe (London), and Asia Pacific (Singapore).