Explains business, technical and operational metadata
Metadata describes data, and whether something is data or metadata depends on its use. Business metadata: terms, definitions, owners, classifications; technical: tables, columns, views, jobs, lineage; operational: load runs, row counts, quality results, freshness (DMBOK2 ch. 12 §1.3.1-1.3.2).
Can AI do this?
AI does this well Most of the tested AI models master this. 3 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 82% | Not shown |
| gpt-6-luna | Low cost | 100% | Mastered |
| claude-haiku-5-5 | Low cost | 100% | Mastered |
Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.
What it looks like in practice
Expected result: Metadata describes data, and whether something is data or metadata depends on its use. Business metadata: terms, definitions, owners, classifications; technical: tables, columns, views, jobs, lineage; operational: load runs, row counts, quality results, freshness (DMBOK2 ch. 12 §1.3.1-1.3.2).
How it is assessed: Answers a written question on the types of metadata correctly
Related knobits
Needed for
- M-101 Recognises a metadata use case with no metadata serving it
- M-103 Recognises a needed metadata type with no source
- M-251 Explains metamodel layers, classes and relationships
All 13 knobits of State the metadata requirements and strategy.
Source: Practice the stage 1 reference and review checklist rest on