Free Lesson
Build a Text-to-SQL Agent Blueprint
60 min
Sep 13, 2026 12:30 PM
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What you'll learn
Frame a Text-to-SQL Question
Turn a natural-language request into clear entities, measures, filters, time periods, and expected results.
Map the Required Data
Identify the approved tables, columns, keys, and relationships the agent needs to generate the SQL.
Add Business Meaning
Document metric definitions, filters, exclusions, time rules, and usage guidance so the SQL matches the intended answer.
Build a Knowledge Graph Map
Connect business entities and relationships so the agent can identify the correct path from a question to the data.
Validate the Generated SQL
Check the selected data, joins, calculations, permissions, and evidence before presenting the answer.
Why this topic matters
Organizations already hold valuable answers in databases, warehouses, and operational systems. Text-to-SQL lets people explore that information through natural-language questions. By combining approved data, business definitions, relationships, permissions, and validation rules, teams can produce answers that are useful, traceable, and ready for responsible business use.
