Rapid Recall Key 32–61

1. Completeness = required presence; Integrity = coherent/valid relationships.
2. Consistency = expected agreement; Uniqueness = one representation per real entity.
3. Accuracy may require trusted comparison, sampling, calibration, re-observation or real-world verification.
4. A business expectation describing how data/operations should behave for useful/compliant operation.
5. A dimension-aligned, testable expression of a DQ requirement.
6. Format conformance; allowed-domain membership; type/range/precision; mapping conformance among value domains.
7. Conditions under which missing values/records are acceptable or unacceptable.
8. Expected conditional agreement across values, records, sets, definitions or time.
9. Every ORDER.CUSTOMER_ID must reference an existing approved Customer.
10. Daily record count must remain within an approved fixed/benchmark range unless explained.
11. Compare with trusted/verified source or reality; use sampling/calibration where appropriate.
12. Plan requirements/causes/options; Do fixes/controls; Check conformance; Act respond/correct/restart.
13. DQ team leads much Plan/Do with stakeholders; business operations/process owners carry major ongoing Check/Act responsibility with DQ support.
14. Threshold breach; new data scope; new DQ requirement; changed rule/standard/expectation.
15. Lack of oversight; Data Entry Processes; Data Processing Functions; System Design; Fixing Previous Issues.
16. Missing awareness/priority/leadership/governance/justification/value measurement.
17. Poor training/usability; weak edit checks; bad list placement; field overloading.
18. No downstream awareness; inconsistent execution; changed/stale rules; changing structures.
19. Missing referential/uniqueness constraints; processing/timing/type design; weak Master/Reference controls.
20. They bypass application rules/controls, may be rushed/untested, create unintended consequences, and often lack audit/change control.
21. Define DQ Framework → Define High Quality Data → Dimensions/Supporting Rules → Initial Assessment → Prioritize Improvements → Improvement Goals → Develop/Deploy DQ Operations.
22. Repeatable operating approach for roles, Governance, methods, standards, measurement, communication and extension of practice.
23. Identify important data and articulate purpose-specific quality expectations using business/process/system/stakeholder context.
24. Many expectations are undocumented and embedded in policy, workflow, edits, code, triggers, standards or SME knowledge.
25. Examine actual critical data, profile/query, compare with rules/expectations, discover issues/relationships and validate with Stewards/SMEs.
26. Undocumented dependencies, implied rules, redundant/contradictory data, and genuine conformance.
27. Current remediation; preventive controls/process improvements; ongoing controls/reporting.
28. Combine data evidence with business impact/risk, criticality, stakeholder needs, cost/benefit and feasibility.
29. Quick hit = immediate low-cost issue response; strategic improvement = root-cause/preventive long-term change.
30. Prevention generally costs less and reduces recurring risk compared with repeated correction.

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