If the SQL Runs, Can You Trust the Data Agent Answer?
A layered evaluation framework covering source choice, semantics, execution, analysis, delivery, offline regression, shadow testing, and observability.
Knowledge path
NL2SQL
Why Stronger Data Agents Need a Semantic Layer
Schema describes data shape. This guide shows how metrics, entities, dimensions, business rules, and verified examples turn meaning into executable contracts.
Five Data Agent Routes: Compare Products by the Work They Own
A practical taxonomy for comparing Data Agents across business Q&A, analysis, data science, multimodal research, and data engineering.
The SQL Ran. Why Is the Answer Still Wrong?
A successful query is not necessarily a defensible business answer. This guide covers semantic, grain, time, status, and version errors—and a practical trust chain.
What Is a Data Agent? Four Practical Tests
A data agent is more than a chatbot that writes SQL. Four practical tests—real environments, multi-step execution, verification, and governance—define its production boundary.