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Accelerate your data workflows with Amazon Redshift Data API persistent sessions
In this post, we'll walk through an example ETL process that uses session reuse to efficiently create, populate, and query temporary staging tables across the full data transformation workflow—all within the same persistent Amazon Redshift database session. You'll learn best practices for optimizing ETL orchestration code, reducing job runtimes by eliminating connection overhead, and simplifying pipeline complexity