Diagnostics — DQ13-001–017
Use only after attempting the practice set.
DQ13-001 — A
Why A wins: Chapter 13 defines quality relative to requirements and purpose: relevant DQ dimensions must meet the consumer need.
Why B/C/D lose: no-null perfection, system-of-record status, and standardization are each only possible conditions; none defines overall fitness.
Source: pp. 424–425.
Confusion pair: Fit for purpose vs technical perfection.
DQ13-002 — B
Why B wins: different uses can require different dimensions or thresholds.
Why A/C/D lose: physical datatype, storage application, and refusal to standardize rules do not explain contextual fitness.
Source: pp. 424–425.
Confusion pair: Contextual quality vs universal score.
DQ13-003 — C
Why C wins: monitoring, standards, issue handling, communication and improvement continue as BAU even after improvement projects end.
Why A/B/D lose: projects are allowed; DQ is not IT-only; an ongoing function can contain temporary projects.
Source: pp. 425–426.
Confusion pair: Function vs project/program.
DQ13-004 — D
Why D wins: reduced risk/cost from poor data is an explicit business driver.
Why A/B/C lose: eliminating variation, replacing Governance, or centralizing databases are not Chapter 13 business drivers.
Source: p. 427.
Confusion pair: Business driver vs implementation tactic.
DQ13-005 — A
Why A wins: measuring, monitoring, and reporting DQ levels is a formal goal.
Why B/C/D lose: 100% accuracy is unrealistic/requirement-insensitive; responsibility is not shifted entirely to IT; historical cleanup does not precede all future controls.
Source: pp. 426–428.
Confusion pair: Goal vs impossible perfection.
DQ13-006 — B
Why B wins: criticality prioritizes data by enterprise/customer importance and risk if wrong.
Why A/C/D lose: equal-depth measurement, easiest-first fixing, and “Master Data only” ignore business impact.
Source: pp. 427–429.
Confusion pair: Criticality vs equal treatment.
DQ13-007 — C
Why C wins: standards-driven means turning stakeholder expectations into measurable standards.
Why A/B/D lose: vendor defaults are not business standards; technical types cannot replace business needs; waiting for complaints is reactive.
Source: p. 428.
Confusion pair: Standards vs tool defaults.
DQ13-008 — D
Why D wins: objective measurement must be repeatable and transparent to stakeholders who judge fitness.
Why A/B/C lose: hiding methods, subjective-only scoring, and reporting only corrected defects undermine transparency and control.
Source: p. 428.
Confusion pair: Objective measurement vs opaque scoring.
DQ13-009 — A
Why A wins: changing the entry process stops recurrence before the defect is created.
Why B/C/D lose: repeated repair is correction, archiving reports is administrative, and lowering a threshold hides rather than prevents defects.
Source: p. 428.
Confusion pair: Prevention vs correction.
DQ13-010 — B
Why B wins: root-cause remediation changes the responsible process/system that creates recurrence.
Why A/C/D lose: record correction, more reporting, or reclassification treats symptoms/visibility rather than cause.
Source: p. 428.
Confusion pair: Root cause vs symptom repair.
DQ13-011 — C
Why C wins: process owners are responsible for quality produced through their business processes; technical teams support/systematically enforce requirements.
Why A/B/D lose: transparency, criticality and service levels are real principles but do not address the ownership denial.
Source: p. 428.
Confusion pair: Process owner vs IT-only ownership.
DQ13-012 — D
Why D wins: measurement without response/remediation commitments at boundaries lacks connection to service levels.
Why A/B/C lose: prioritization, standards, and transparent measures do not by themselves establish response obligations.
Source: p. 428.
Confusion pair: Measurement vs SLA commitment.
DQ13-013 — A
Why A wins: a CDE is critical because failure materially damages business/customer/regulatory/financial/reputational outcomes.
Why B/C/D lose: storage size, novelty, and user count are technical/popularity clues rather than impact.
Source: pp. 428–429.
Confusion pair: Criticality vs technical prominence.
DQ13-014 — B
Why B wins: Master/Reference Data is widely reused, so defects propagate across processes, reports and controls.
Why A/C/D lose: single-database storage is not required; the data is not exempt from measurement and can contain duplicates.
Source: p. 429.
Confusion pair: Criticality vs storage architecture.
DQ13-015 — C
Why C wins: type/range/format/precision/domain conformance is Validity.
Why A/B/D lose: reality = Accuracy; delivery time = Timeliness; required presence = Completeness.
Source: pp. 429–430.
Confusion pair: Validity vs Accuracy.
DQ13-016 — D
Why D wins: Completeness asks whether required values/records are present under applicable conditions.
Why A/B/C lose: parent reference = Integrity; reality = Accuracy; elapsed availability = Timeliness.
Source: p. 430.
Confusion pair: Completeness vs Integrity.
DQ13-017 — A
Why A wins: Consistency tests expected agreement across values, records, data sets or time.
Why B/C/D lose: one-per-entity = Uniqueness; current enough = Currency; reality = Accuracy.
Source: pp. 430–431.
Confusion pair: Consistency vs Uniqueness.