claude-fable-5-1
claude-fable-5-1 masters 148 of the 199 benchmarked knobits of Data modelling: an expected 92% of the competence.
Data modelling, activity by activity
| Activity | Test score | Knobits mastered (expected) |
|---|---|---|
| Capture data requirements | 75% | 78% |
| Define business terms | 92% | 99% |
| Document data rules as SBVR fact types and rule statements | 88% | 98% |
| Build the conceptual model and taxonomies | 100% | 100% |
| Derive the logical data model | 88% | 94% |
| Design the physical data model | 98% | 98% |
| Derive data quality rules | 83% | 95% |
| Generate and review DDL | 70% | 73% |
Where it falls short
The knobits with the lowest probability of mastery: review its output here most carefully.
- K-103 Recognises a statement outside the scope of data requirements 0%
- K-816 Recognises one decimal scale for every currency 0%
- K-803 Recognises an object in the SQL missing from the model 0%
- K-718 Recognises a misfiled data quality dimension 19%
- K-117 Recognises a missing or wrong requirement type 21%
- K-810 Recognises a truncated identifier taken as the real name 21%
- K-821 Recognises a restricted column without access design 23%
- K-822 Recognises greenfield DDL aimed at a populated database 27%
- K-823 Recognises a drop script used as a rollback 27%
- K-123 Recognises conflicting data requirements 37%
- K-122 Recognises paraphrased data requirements 38%
- K-121 Recognises duplicate data requirements 38%
- K-808 Recognises a CHECK constraint parsed and ignored 38%
- K-820 Recognises a default inventing a business fact 39%
- K-116 Recognises a missing or meaningless requirement priority 40%