
SageMaker Data Agent in Query Editor enables users to generate SQL queries for Amazon Redshift and Athena using natural language prompts, with catalog awareness, session context, step-by-step planning, and AI-powered error recovery.


<div><p>This article introduces SageMaker Data Agent in Query Editor, which enables natural language SQL generation for Amazon Redshift and Athena without manual query writing.</p><ul><li>Converts natural language questions to executable SQL in seconds</li><li>Reads AWS Glue Data Catalog metadata for accurate table and column references</li><li>Retains session context across multiple queries for iterative analysis</li><li>Proposes step-by-step plans for complex analytical questions</li><li>Offers one-click error recovery with "Fix with AI" functionality</li><li>Operates within existing IAM and AWS Lake Formation security controls</li><li>Includes content filtering and restricts output to AWS topics and English</li></ul><p>The walkthrough demonstrates exploring education data, building multi-step analyses, summarizing insights, and recovering from query failures using natural language prompts in Query Editor.</p></div>


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