Explains the business drivers and goals of data governance
Regulatory compliance, risk reduction and improved data use as drivers; goals of sustainability, embedding and measurability.
Can AI do this?
Not settled yet The benchmark tested this, but the models' answers do not settle yet whether they master it. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 49% | Not shown |
| gemini-3.5-flash-lite | Low cost | 49% | Not shown |
| gpt-6-luna | Low cost | 49% | Not shown |
| claude-haiku-5-5 | Low cost | 49% | 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: Regulatory compliance, risk reduction and improved data use as drivers; goals of sustainability, embedding and measurability.
How it is assessed: Answers a CDMP-style multiple-choice question on the business drivers of data governance
All knobits of Data governance.
Source: DAMA-DMBOK2 chapter 3, element GV-1