Explains data flows and the data value chain
Flows with source, target, entities, frequency, pattern and deletions; every consumer copy traced back to the record.
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 | 98% | 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: Flows with source, target, entities, frequency, pattern and deletions; every consumer copy traced back to the record.
How it is assessed: Answers a written question on the data flow and value chain correctly
Related knobits
Builds on
Needed for
- A-305 Recognises a data flow with no consumer
- A-306 Recognises a data flow into the system of record
- A-307 Recognises a deletion not reaching the copies
- A-308 Recognises a flow of data its source does not hold
- A-310 Recognises a broken data value chain
- A-311 Recognises a data flow with no frequency or pattern
- A-312 Recognises a circular data flow
All 15 knobits of Map data flows and the CRUD matrix.
Source: Practice the stage 3 reference and review checklist rest on