Recognises a data quality issue owner unable to fix its cause
The issue assigned to someone without authority over the cause.
Can AI do this?
People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 90% | Not shown |
| gemini-3.5-flash-lite | Low cost | 83% | Not shown |
| gpt-6-luna | Low cost | 83% | Not shown |
| claude-haiku-5-5 | Low cost | 90% | 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: The owner of the cause, with the data owner accountable
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: IS-001 owner "Data quality analyst"; cause CA-001/MP-311 is the migration mapping Acceptable: Migration lead fixes MP-311; Retail lending data owner accountable
Also known as: Owner who cannot fix the cause
Related knobits
Builds on
All 9 knobits of Manage data quality issues.
Source: Review checklist 06-issue-management, row 2 (ITIL (problem owner); DMBOK)