Amazon SageMaker Catalog now supports read and write access to Amazon S3

Amazon SageMaker Catalog Updates

Amazon SageMaker Catalog now supports read and write access to Amazon S3 general purpose buckets. This enhancement enables data scientists and analysts to search for unstructured data, process it alongside structured datasets, and share transformed datasets with other teams. Data publishers gain additional controls to support analytics and generative AI workflows within SageMaker Unified Studio while maintaining security and governance controls over shared data.

When approving subscription requests or directly sharing S3 data within the SageMaker Catalog, data producers can choose to grant read-only or read and write access. If granted read and write access, data consumers can process datasets in SageMaker and store the results back to the S3 bucket or folder. The data can then be published and automatically discoverable by other teams.

What to do

• Log into SageMaker Unified Studio to start using the new feature.
• Use the Amazon DataZone API, SDK, or AWS CLI to manage access and permissions.
• Refer to the SageMaker Unified Studio guide for more information.

This capability is now available in all AWS Regions where Amazon SageMaker Unified Studio is supported.

Source: AWS release notes

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