Genie Ontology helps Genie One and Genie Agents use business context from governed data, semantic definitions, and existing work assets. The most practical way to improve answer quality is to strengthen that foundation progressively, one business domain at a time.
A six-layer path to better answers
- Layer 0 | Build a solid data foundation: Start with clean tables, clear schemas, reliable business grain, and consistent entities. Resolve duplicate identities and shape trusted consumption surfaces before asking agents to reason across the estate.
- Layer 1 | Enrich metadata: Add useful table descriptions, column comments, and governed tags in Unity Catalog. Tools such as dbxmetagen can help generate a first pass, while human review keeps the final metadata accurate.
- Layer 2 | Model business meaning: Define relationships, critical metrics, dimensions, synonyms, and formatting with Unity Catalog metric views. Use Domains to organize assets and Pages to document authoritative business concepts.
- Layer 3 | Curate context-rich assets: Make dashboards, notebooks, queries, and Genie Agents useful sources of context by documenting them, adding examples, and keeping them current. Certification and deprecation help signal which assets are trusted and which should no longer guide users or agents.
- Layer 4 | Apply governance: Use Unity Catalog permissions and fine-grained controls to govern access to data and context. Unity AI Gateway adds a central control point for AI services, model access, policies, and usage.
- Layer 5 | Evaluate and improve: Create realistic questions for each priority domain, compare answers with known results, inspect generated SQL and citations, and use feedback to fix the right layer. Genie Agent monitoring and benchmarks provide a repeatable way to track quality and usage over time.
๐ Read the full post here
