AWS Clean Rooms supports minimum aggregation thresholds in custom analysis rules

AWS Clean Rooms has introduced support for minimum aggregation thresholds in Custom analysis rules, allowing data providers to set limits on query outputs to safeguard individual privacy. Previously, enforcing such thresholds required pre-approved templates and manual reviews, but now providers can configure these rules directly within custom SQL queries. The feature enables automatic filtering of small datasets, such as rural zip codes with fewer than 1,000 common users, to prevent disclosure of identifiable information.

Data providers can specify identity columns and minimum counts for query outputs, with the option to apply higher thresholds to specific columns. This enhancement streamlines collaboration by eliminating the need for pre-structured queries or manual approval processes, enabling faster and more flexible data analysis. The feature also allows providers to control which columns can be filtered or joined across datasets, improving data governance and compliance.

The update applies to AWS Clean Rooms, a service designed to help companies and their partners analyze shared datasets without exposing underlying data. Organizations can now enforce privacy protections while maintaining the ability to run ad-hoc queries, reducing operational overhead and accelerating decision-making. The feature is available in all AWS Regions where AWS Clean Rooms operates.

AWS Clean Rooms supports minimum aggregation thresholds for Custom analysis rules, enabling data providers to enforce privacy protections directly within custom SQL queries. This change reduces reliance on manual reviews and pre-approved templates, allowing for more efficient and secure data collaboration. The feature is part of AWS Clean Rooms' ongoing efforts to balance data utility with privacy protections for collaborative analysis.