Explains the master data stewardship workflow
Queues for clerical review, survivorship conflicts and reference data changes, each with owner, SLA, escalation, capacity and an audit of decisions (DMBOK2 ch. 10).
Can AI do this?
AI does this well Most of the tested AI models master this. 4 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 | 100% | Mastered |
| 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: Queues for clerical review, survivorship conflicts and reference data changes, each with owner, SLA, escalation, capacity and an audit of decisions (DMBOK2 ch. 10).
How it is assessed: Answers a written question on the stewardship workflow correctly
Related knobits
Needed for
- R-501 Recognises a stewardship queue with no owner
- R-502 Recognises a stewardship SLA the staffing cannot meet
- R-505 Recognises unaudited steward decisions
- R-508 Recognises a stewardship queue with no escalation
- R-531 Computes stewardship queue capacity from the statistics
- R-533 Uses only the staffing figures given
All 13 knobits of Run the stewardship workflow and measure MDM.
Source: Practice the stage 5 reference and review checklist rest on