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The following figure shows an example diagram that illustrates an orchestrated extract, transform, and load (ETL) architecture solution. For example, searching for the terms “How to orchestrate ETL pipeline” returns results of architecture diagrams built with AWS Glue and AWS Step Functions.
IAM role – SageMaker requires an AWS Identity and Access Management (IAM) role to be assigned to a SageMaker Studio domain or user profile to manage permissions effectively. Create database connections The built-in SQL browsing and execution capabilities of SageMaker Studio are enhanced by AWS Glue connections. or later image versions.
Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. You can use familiar AWS services for model development, generative AI, data processing, and analyticsall within a single, governed environment.
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