Explains grain and additivity in dimensional models
One row means one thing; measures are additive, semi-additive or non-additive.
Can AI do this?
AI does this well Most of the tested AI models master this. 7 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 33% | Not shown |
| gpt-6-astra | Flagship | 100% | Mastered |
| claude-fable-5-1 | Flagship | 100% | Mastered |
| gemini-3.8-flash | Mid tier | 100% | Mastered |
| gpt-6.1-sol | Mid tier | 100% | Mastered |
| claude-sonnet-5-5 | Mid tier | 100% | Mastered |
| gemini-3.5-flash-lite | Low cost | 33% | Not shown |
| gpt-6-luna | Low cost | 83% | Not shown |
| 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: One row means one thing; measures are additive, semi-additive or non-additive
How it is assessed: States the grain of sample fact tables and the additivity of their measures
Related knobits
Builds on
Needed for
All 40 knobits of Design the physical data model.
Source: Data-management practice used by the stage 6 reference and review checklist