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An integrated experience for all your data and AI with Amazon SageMaker Unified Studio (preview)

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As AI and analytics use cases converge, transform how data teams work together with SageMaker Unified Studio. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. She is passionate about helping customers build data lakes using ETL workloads. Big Data Architect.

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

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About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is responsible for building software artifacts to help customers. In his spare time, he enjoys cycling with his road bike. Vishal Kajjam is a Software Development Engineer on the AWS Glue team.

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Simplify data access for your enterprise using Amazon SageMaker Lakehouse

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With unified access, you can use preferred analytics, machine learning, and business intelligence engines through an open, Apache Iceberg REST API and secure access to data with consistent, fine-grained access controls. About the Authors Srividya Parthasarathy is a Senior Big Data Architect on the AWS Lake Formation team.

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Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark

AWS Machine Learning Blog

This enables you to preprocess your external data in the phases including cleaning, sanitization, chunking documents, generating vector embeddings for each chunk, and loading into a vector store. About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

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