Explains the source-to-target mapping contract
Per target column: source fields, transformation, default, crosswalk and rule; every mandatory target mapped; keys qualified by source; reconciled on value (DMBOK2 ch. 8).
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 | 99% | 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: Per target column: source fields, transformation, default, crosswalk and rule; every mandatory target mapped; keys qualified by source; reconciled on value (DMBOK2 ch. 8).
How it is assessed: Answers a written question on the source-to-target mapping correctly
Related knobits
Needed for
- K-820 Recognises a default inventing a business fact
- N-201 Recognises an unmapped mandatory target column
- N-205 Recognises a key collision across sources
- N-207 Recognises a mapping ignoring a meaning change
- N-210 Recognises an unspecified transformation
- N-211 Recognises a target narrower than its source
- N-212 Recognises a transformation on a column the source lacks
- O-501 Recognises a reconciliation by count only
- O-503 Recognises a source value with no target value
All 18 knobits of Map sources to targets.
Source: Practice the stage 2 reference and review checklist rest on