Remove 2012 Remove Data Preparation Remove ETL
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Explore data with ease: Use SQL and Text-to-SQL in Amazon SageMaker Studio JupyterLab notebooks

AWS Machine Learning Blog

These connections are used by AWS Glue crawlers, jobs, and development endpoints to access various types of data stores. You can use these connections for both source and target data, and even reuse the same connection across multiple crawlers or extract, transform, and load (ETL) jobs. or later image versions.

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Connect, share, and query where your data sits using Amazon SageMaker Unified Studio

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Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. Users can write data to managed RMS tables using Iceberg APIs, Amazon Redshift, or Zero-ETL ingestion from supported data sources.

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