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Confusion Matrix, Changed-Fact Drills & Cram Route

High-risk confusion matrix

Pair Deciding distinction Changed-fact clue
Validity vs Accuracy formal rule/domain vs reality formatted email belongs to wrong person → valid form, inaccurate
Timeliness vs Currency delivery delay vs currentness on-time three-day-old balances → timely delivery, poor currency
Completeness vs Integrity required presence vs valid relationship populated orphan FK → integrity
Consistency vs Uniqueness agreement vs one-per-entity duplicate customer → uniqueness
Profiling vs DQ Rule observed statistic vs approved expectation 12% nulls vs ≥99% must be populated
Initial Assessment vs Monitoring baseline discovery vs repeated control first investigation vs daily scorecard
Correction vs Root Cause repair record vs remove recurrence cause fix rows vs change UI/process
DQ SLA vs Scorecard service commitment vs summarized condition resolve within 4 hours vs completeness 97%
Parse vs Standardize vs Enrich decompose vs change representation vs add split name vs normalize vs add geocode
DQ Function vs Project continuing capability vs temporary initiative project ends; function persists

Twelve changed-fact drills

  1. Email quality: 98% populated, requirement 95% → completeness passes. If 40% bounce → accuracy becomes larger problem.
  2. Supplier file: arrives at 8 a.m. but contains last week’s customers → timeliness may pass; currency fails. Current values arriving noon → timeliness fails.
  3. Customer master: two IDs, same identity → uniqueness. Single record with another customer’s address → accuracy.
  4. Order records: CUSTOMER_ID populated but parent missing → integrity. CUSTOMER_ID null → completeness.
  5. Profile finding: 7% STATE null → potential issue only. Approved optional rule may make nulls valid.
  6. Issue response: 50k rows corrected monthly → correction, cause likely remains. Unchangeable upstream with cheaper controlled correction can justify ongoing correction.
  7. Incident workflow: severe issue unassigned → assignment/escalation failure. Ownership clear but obsolete rule → rule management.
  8. SLA: quality threshold exists but notification/deadline absent → incomplete SLA. Commitments exist but no measurement → measure/monitor gap.
  9. Parsing: free-form name must be decomposed → parsing. Components known but need enterprise format → standardization.
  10. Correction confidence: proposed fixes with confidence + Steward review → manually-directed. Deterministic auto-commit → fully automated.
  11. Readiness: leaders support DQ but actual state unknown → build objective state first. State/risk/priorities known → broader program more feasible.
  12. Governance: reports show failures but business units cannot agree priority/ownership → Governance. Ownership agreed but processing defect remains → process/system remediation.

Decision-clue route

  1. Identify threatened business use/consumer requirement.
  2. Decide whether stem is about criticality, dimension, rule, measurement, issue, or improvement/control.
  3. Classify exact dimension failure before selecting a tool or fix.
  4. Determine baseline assessment vs ongoing control.
  5. Separate symptom correction from root-cause prevention.
  6. Identify accountable owner/decision mechanism.
  7. Select tool/technique/artifact last.

10-minute cram route

  • 0–2: fit for purpose + nine dimensions.
  • 2–4: eight principles + criticality.
  • 4–6: PDCA + seven activities.
  • 6–8: rule management, monitoring, issues, SLA, response.
  • 8–10: profiling/RCA, prevention/correction, tool distinctions, Governance links.

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