Explains the feasibility of BI requirements against sources
What the sources can deliver: the data they capture, their grain, refresh times and retention (ISO/IEC/IEEE 29148 feasibility).
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 | 92% | 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: What the sources can deliver: the data they capture, their grain, refresh times and retention (ISO/IEC/IEEE 29148 feasibility).
How it is assessed: Answers a written question on the BI requirement feasibility correctly
Related knobits
Needed for
- W-102 Recognises a BI question the data cannot answer
- W-103 Recognises a grain coarser than the question
- W-104 Recognises timeliness the sources cannot meet
- W-108 Recognises history beyond what the sources keep
- W-132 Raises a timeliness gap against the source refresh
All 13 knobits of Capture BI requirements.
Source: Practice the stage 1 reference and review checklist rest on