Explains source-to-target mappings as lineage edges
An integration edge cites the data-integration mapping it implements, which holds the transformation logic; an edge inside the warehouse carries its job or view logic, never a placeholder.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 98% | Not shown |
| gemini-3.5-flash-lite | Low cost | 98% | Not shown |
| gpt-6-luna | Low cost | 98% | Not shown |
| claude-haiku-5-5 | Low cost | 98% | Not shown |
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: An integration edge cites the data-integration mapping it implements, which holds the transformation logic; an edge inside the warehouse carries its job or view logic, never a placeholder.
How it is assessed: Answers a written question on the source-to-target mapping correctly
Related knobits
Builds on
Needed for
- M-504 Recognises a lineage edge with placeholder logic
- M-505 Recognises an integration lineage edge without its mapping
All 11 knobits of Trace column-level lineage.
Source: Practice the stage 5 reference and review checklist rest on