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Simplify data integration with AWS Glue and zero-ETL to Amazon SageMaker Lakehouse

AWS Big Data

With the growing emphasis on data, organizations are constantly seeking more efficient and agile ways to integrate their data, especially from a wide variety of applications. We take care of the ETL for you by automating the creation and management of data replication. Glue ETL offers customer-managed data ingestion.

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Author visual ETL flows on Amazon SageMaker Unified Studio (preview)

AWS Big Data

From the Unified Studio, you can collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics. This experience includes visual ETL, a new visual interface that makes it simple for data engineers to author, run, and monitor extract, transform, load (ETL) data integration flow.

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Introducing generative AI upgrades for Apache Spark in AWS Glue (preview)

AWS Big Data

About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. Keerthi Chadalavada is a Senior Software Development Engineer at AWS Glue, focusing on combining generative AI and data integration technologies to design and build comprehensive solutions for customers’ data and analytics needs.

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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity.

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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

SageMaker brings together widely adopted AWS ML and analytics capabilities—virtually all of the components you need for data exploration, preparation, and integration; petabyte-scale big data processing; fast SQL analytics; model development and training; governance; and generative AI development.

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Take manual snapshots and restore in a different domain spanning across various Regions and accounts in Amazon OpenSearch Service

AWS Big Data

It covers the essential steps for taking snapshots of your data, implementing safe transfer across different AWS Regions and accounts, and restoring them in a new domain. This guide is designed to help you maintain data integrity and continuity while navigating complex multi-Region and multi-account environments in OpenSearch Service.

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Scaling RISE with SAP data and AWS Glue

AWS Big Data

By using the AWS Glue OData connector for SAP, you can work seamlessly with your data on AWS Glue and Apache Spark in a distributed fashion for efficient processing. AWS Glue OData connector for SAP uses the SAP ODP framework and OData protocol for data extraction. Choose Confirm to confirm that your job will be script-only.