Practice — DQ13-052–068
DQ13-052 — Operations & SLA · Standard · Apply
A DQ incident is logged but has no accountable person or team responsible for progress. Which issue-management element is missing? - A. Profiling. - B. Enrichment. - C. Data standardization. - D. Assignment/ownership.
DQ13-053 — Operations & SLA · Standard · Apply
When should a DQ issue be escalated? - A. When its impact, urgency, duration, risk, or inability to resolve at the current level warrants higher authority/action. - B. Every time a single invalid record is found. - C. Only after the issue has already been corrected. - D. Never; Data Stewards must resolve all issues themselves.
DQ13-054 — Operations & SLA · Standard · Apply
A recurring reporting defect is traced backward through lineage to an upstream calculation error. Which issue-management work is being performed? - A. Only scorecard reporting. - B. Diagnosis/root-cause analysis. - C. Data enrichment. - D. SLA negotiation.
DQ13-055 — Operations & SLA · Difficult · Distinguish
Which statement best reflects Chapter 13's approach to remediation decisions? - A. Always correct every defective record regardless of cost or impact. - B. Always choose a technical fix because DQ is a technical discipline. - C. Evaluate alternatives—including process/system/control changes, direct correction, or even no action—using costs, benefits, risk, and business-owner input. - D. Never accept a defect after it has been measured.
DQ13-056 — Operations & SLA · Standard · Recall
What does a Data Quality Service Level Agreement primarily specify? - A. Only the licensing terms for a Data Quality tool. - B. Only the number of fields a profiling job must scan. - C. A complete replacement for Data Governance policies. - D. Agreed quality expectations plus response/remediation commitments for DQ issues at important organizational/process boundaries.
DQ13-057 — Operations & SLA · Difficult · Apply
Which set of items belongs most naturally in a Data Quality SLA? - A. Covered data, business impact, dimensions/rules, measurement method, thresholds, notification, response/remediation times, and escalation. - B. Only data model diagrams and server inventory. - C. Only current defect counts with no thresholds or commitments. - D. Only business glossary definitions with no measurement method.
DQ13-058 — Operations & SLA · Standard · Understand
Why is Data Quality Response/reporting necessary? - A. Because reporting itself corrects defective records. - B. Assessment and issue work create little value if consumers cannot see data condition, trends, SLA performance, issue status, and improvement effects. - C. Because every DQ metric must be made public to all users. - D. Because scorecards replace the need for issue management.
DQ13-059 — Operations & SLA · Standard · Distinguish
Which artifact is the best fit for a high-level view of quality scores against thresholds across multiple data domains? - A. A single incident ticket. - B. A parsing specification. - C. A Data Quality scorecard. - D. A root-cause fishbone diagram.
DQ13-060 — Operations & SLA · Standard · Apply
A supplier SLA includes monthly penalties for repeated threshold failures. Which reporting approach is especially important? - A. A one-time profile only. - B. A catalog of table definitions only. - C. A manual correction log with no quality measures. - D. Trend analysis over time against the SLA thresholds and commitments.
DQ13-061 — Tools & Techniques · Standard · Distinguish
What is the primary role of a Data Profiling tool? - A. Analyze data content, distributions, patterns, relationships, and anomalies to understand actual conditions. - B. Define enterprise business ownership automatically. - C. Guarantee accuracy against reality without any trusted comparison source. - D. Replace Data Quality rules with vendor defaults.
DQ13-062 — Tools & Techniques · Standard · Apply
A free-form NAME field is decomposed into title, first name, middle name, surname, and suffix. Which tool capability is being used? - A. Data enrichment. - B. Data parsing and formatting. - C. Incident management. - D. Root-cause analysis.
DQ13-063 — Tools & Techniques · Standard · Apply
Values 'Tennessee', 'Tenn.', and 'TN' are converted to the approved representation 'TN'. Which capability is primary? - A. Data profiling only. - B. Data enrichment. - C. Data transformation and standardization. - D. Issue escalation.
DQ13-064 — Tools & Techniques · Standard · Apply
An organization adds geocodes and demographic attributes from a trusted external source to existing address records. Which capability is primary? - A. Parsing. - B. Uniqueness measurement. - C. SLA escalation. - D. Data enrichment.
DQ13-065 — Tools & Techniques · Difficult · Distinguish
Which characteristic makes a Data Quality metric most useful for management? - A. It is measurable, business relevant, tied to an acceptance threshold and accountability, actionable/controllable, and trendable. - B. It produces the largest possible number of decimal places. - C. It is defined by the profiling tool without stakeholder agreement. - D. It measures every available column even if none is business critical.
DQ13-066 — Tools & Techniques · Standard · Distinguish
A correction engine automatically fixes high-confidence records but routes ambiguous cases to a Data Steward. Which correction mode is this? - A. Fully automated correction. - B. Manually-directed correction. - C. Direct manual production patching. - D. Data profiling.
DQ13-067 — Implementation & Governance · Standard · Apply
Which implementation approach does Chapter 13 say typically works best for establishing a Data Quality Function? - A. Purely top-down, with no local defect discovery. - B. Purely bottom-up, with no enterprise sponsorship or standards. - C. A hybrid: top-down sponsorship, consistency, and resources combined with bottom-up discovery and incremental wins. - D. Tool-first implementation with governance added after rollout.
DQ13-068 — Implementation & Governance · Expert-discrimination · Apply
A regulatory customer identifier is critical. Profiling shows it is 99.8% populated, but 6% of populated values point to no valid master Customer record. The feed arrives on time. What is the best next interpretation and action? - A. The data is high quality because 99.8% completeness exceeds 99%. - B. The issue is Timeliness because the feed is part of a scheduled integration. - C. Correct the 6% of records manually and close the issue without investigating the process. - D. The deciding DQ failure is Integrity, not simple Completeness or Timeliness; confirm the rule/threshold with Stewards, trace the root cause through the producing process/system, prioritize remediation because the element is critical, and establish ongoing monitoring/control.