Discover how Amazon SageMaker Unified Studio enables users to find governed data using natural language without knowing exact table names, then turn those discoveries into automated SQL for analysis. In this demo, learn how to search for business concepts like “customers likely to leave the bank” and receive related data assets enriched with business names, descriptions, and glossary terms. See how the SageMaker Data Agent transforms business questions into automated SQL code by identifying the right tables, generating proper joins, and excluding personally identifiable information. Explore how to create SQL notebooks and use AI to generate code that breaks down results by customer segment or region, then review, refine, or run the generated queries without manually remembering table names and join paths. This workflow demonstrates how data discovery and automated code generation work together to accelerate analysis across any domain.
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