Recognises a declared constraint the target platform does not enforce
Snowflake and Databricks accept constraint syntax and enforce none of it, so every rule marked constraint there is unenforced.
Can AI do this?
AI does this well Most of the tested AI models master this. 10 of 10 models master it.
| Model | Tier | Probability of mastery | Status |
|---|---|---|---|
| gemini-4-argon | Flagship | 100% | Mastered |
| gemini-3.1-pro-preview | Flagship | 100% | Mastered |
| 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 | 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: The constraint, the fact nothing enforces it, and the data quality check it needs
How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: enforcement: constraint on a Snowflake target, with nothing else Acceptable: A DQ rule citing it as well, so the load is the guarantee and the check reports breaches (DQR-017)
Also known as: Rule lost to a non-enforcing platform (data rule); Constraint the platform does not enforce (physical model); Constraint the platform does not enforce, with no check (data quality rule); `-- NOT ENFORCED` read as a guarantee (generated DDL)
Related knobits
Builds on
All 28 knobits of Document data rules as SBVR fact types and rule statements.
Source: Review checklist 03-data-rules, row 13