Rapid Discrimination Cards 01–20
- DQ vs Data Cleansing — DQ Management is the ongoing function; cleansing is one corrective technique.
- Fit for purpose vs perfect data — quality is contextual/requirement-driven; perfection is not the target.
- Function vs Project — function continues; project has defined start/end inside the function.
- Criticality vs Volume — business/risk impact vs sheer amount/frequency.
- Dimension vs Rule — dimension names the quality characteristic; rule states the testable requirement.
- Rule vs Metric — rule defines expectation/test; metric reports measured conformance.
- Metric vs Threshold — metric is the score; threshold is the acceptability cutoff.
- Validity vs Accuracy — conforms to domain/rule vs matches reality.
- Completeness vs Integrity — required data present vs relationships/coherence intact.
- Timeliness vs Currency — delay until available vs whether still current.
- Consistency vs Accuracy — agreement of representations vs real-world correctness.
- Consistency vs Uniqueness — agreement across values/sets/time vs one representation per real entity.
- Reasonableness vs Validity — plausible/expected pattern vs formal domain/range/format.
- Uniqueness vs Referential Integrity — duplicate entities vs broken parent-child relationships.
- Initial Assessment vs Monitoring — baseline discovery vs repeated operational control.
- Profiling vs Rule Testing — discover patterns vs evaluate approved expectations.
- Profiling vs RCA — surface potential issues vs explain why they happen.
- Correction vs Prevention — repair existing defects vs stop defects being created/propagated.
- Root-cause remediation vs Symptom fix — remove cause vs repeatedly treat manifestation.
- Plan vs Do — analyze/prioritize/plan vs implement changes/controls.
Speed check
For Cards 8–19, give one scenario where the left side wins and one changed fact that makes the right side win.