Governed Business Data Agents

Governed business data agents answer or act over enterprise data through validated semantic layers, metrics, and definitions instead of ad-hoc database access.

Key points

  • Google Cloud's Looker + MCP explainer argues that agents need a governed semantic layer to understand business context [src-139].
  • Using Looker through MCP reduces the risk of fragile raw SQL and inconsistent metric definitions [src-139].
  • This is a practical pattern for decisioning systems: agents need approved business meaning before they can be trusted with analysis.

Related entities

Related concepts

Source references

  • [src-139] Google Cloud Tech – "Governed agents: Looker + MCP explained" (2026-06-19)

2026-07-17 data-quality update

  • Decathlon's CDO argues that agents do not reliably apply human scepticism to questionable data, so domain ownership, contracts, lineage, tests, and quality monitoring are prerequisites for trusted action [src-243].
  • Governance therefore needs to execute before or during agent consumption, not arrive as a retrospective audit [src-243].

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

Recommended next

Keep reading from this thread

From 500 indexed pages and articles.

  1. Wiki concept Enterprise AI Governance Covers the controls and operating practices used to manage AI risk, access, data exposure, compliance, and reliability at scale. Related by 243
  2. Wiki concept Semantic Contracts for Agents Loose, intent-level expectations governing agent handoffs and outcomes, used when rigid schemas are insufficient for dynamic agent behavior. Related by semantic
  3. Wiki concept Data Agents AI agents embedded into data platforms to help analysts, engineers, scientists, and database administrators query, build, monitor, and remediate data workflows Related by data