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Amazon SageMaker Lakehouse now supports attribute-based access control
- Amazon SageMaker Lakehouse now supports attribute-based access control (ABAC) with AWS Lake Formation, using IAM principals and session tags for simplified data access and maintenance.
- Attribute-based access control (ABAC) in SageMaker Lakehouse allows organizations to create dynamic access control policies based on business attributes associated with user identities.
- SageMaker Lakehouse provides unified access to various data sources like Amazon S3, Redshift, DynamoDB, and supports querying using services like Redshift, Athena, EMR, and Glue.
- ABAC offers flexibility in managing access rules, reducing administrative overhead by handling a smaller number of roles, and scalability for larger enterprises with numerous users and resources.
- ABAC grants permissions based on user attributes and is context-driven, enabling administrators to restrict data access based on specific user attribute keys and values.
- By using ABAC, organizations can reduce the number of roles required, grant access based on attributes like department or country, and easily create and maintain data access grants.
- The implementation involves defining user attributes using IAM tags, setting access policies in Lake Formation, and granting permissions based on the predefined criteria.
- The solution architecture includes defining attributes, setting up ABAC policies, and granting database and table permissions to users based on their attributes.
- Users like data analysts, BI analysts, and data scientists can leverage ABAC in SageMaker Lakehouse for specific data access based on their roles and attributes.
- The post demonstrates setting up ABAC for Example Retail Corp, granting specific data access permissions to different user personas, and utilizing analytics services like Athena, Redshift, and EMR.
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