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Amazon S3 Tables integration with Amazon SageMaker Lakehouse is now generally available
- Amazon S3 Tables, integrated with Apache Iceberg, and Amazon SageMaker Lakehouse were launched to simplify tabular data storage and analytics collaboration.
- S3 Tables integration with AWS analytics services like Amazon Athena, EMR, Redshift, and others allows for streamlined querying and visualization of data.
- Customers can leverage S3 Tables and SageMaker Lakehouse for unified access to multiple data sources, enhancing analytics and machine learning workflows.
- The general availability of Amazon S3 Tables integration with Amazon SageMaker Lakehouse enables unified data access across various analytics engines.
- Users can centrally manage access permissions on S3 Tables data, Redshift, and other sources within SageMaker Lakehouse for secure analytic workflows.
- To get started with S3 Tables integration, users can create table buckets and access them from AWS analytics services like Amazon Athena.
- Integration with Amazon SageMaker Unified Studio enables querying S3 data lakes, Redshift, and other sources directly within SageMaker Lakehouse.
- Data engineers can join S3 Tables data with data from various sources, such as DynamoDB and Redshift, to gain deeper insights without ETL scripts.
- The availability of S3 Tables integration with SageMaker Lakehouse in all AWS Regions offers users a unified data access experience.
- Users are encouraged to try out S3 Tables in SageMaker Unified Studio and provide feedback for further enhancements.
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