Explains dimensional modelling
Fact and dimension tables, star and snowflake schemas, conformed dimensions and facts.
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 | 67% | 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 | 67% | Not shown |
| gpt-6-luna | Low cost | 92% | 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: Fact and dimension tables, star and snowflake schemas, conformed dimensions and facts
How it is assessed: Identifies the facts, dimensions and conformed dimensions of a sample star schema and says when to snowflake
Related knobits
Needed for
- K-659 Explains grain and additivity in dimensional models
- K-913 Explains how to choose a modelling scheme and notation
All knobits of Data modelling.
Source: DAMA-DMBOK2 chapter 5, section 1.3.4.2