Recently, many teams have been working on Text-to-SQL, ChatBI, or data analysis agents. One often underestimated issue is that generating SQL is only the first step—deterministic semantic, permission, and audit checks must also be conducted before deployment.
This article discusses a readiness checklist for teams preparing to move LLM-generated SQL from experimentation to production, assessing whether governance capabilities are in place.
Key Points:
Governance readiness encompasses not only SQL generation quality but also validation, permission checks, lineage, and auditability.
LLM-generated SQL should be tested within the context of real catalogs and policy frameworks.
The article provides a checklist suitable for architecture reviews and pre-deployment inspections.
Original Link: https://www.dpriver.com/blog/how-to-evaluate-sql-governance-readiness-for-llm-generated-queries/?utm_source=dev&utm_medium=community&utm_campaign=ai_sql_governance_external_2026q2&utm_content=shenhuan_dev_how_to_evaluate_sql_governance_readiness_for_llm_generated_queries
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