Free DAMA CDMP Quality Practice Questions: Root Cause Analysis and Remediation

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These are original IT Mastery practice questions aligned to this topic area. They are not official exam questions, copied live-exam content, or exam dumps. Use them for self-assessment, scope review, and deciding what to drill next.

Question 1

Topic: Root Cause Analysis and Remediation

A data quality defect was opened after duplicate customer records caused duplicate invoices. Remediation changed the customer onboarding validation and the merge rule in the master data hub. Governance-approved closure criteria require evidence that the source process was corrected, impacted records were remediated, and duplicate-invoice exceptions stayed below 0.5% for two monthly billing cycles. Which evidence best supports closing the defect?

Options:

• A. A steward approval note stating that users are satisfied with the cleanup

• B. Two monthly control reports with validation active, merges completed, and exceptions at 0.2% and 0.1%

• C. A one-time profile showing no duplicate customer records after cleansing

• D. A development test showing the new merge rule blocks duplicate customer IDs

Best answer: B

Explanation: Defect closure should be supported by validation evidence tied to the agreed closure criteria, not just proof that an activity occurred. Here, closure requires three things: the source process correction is operating, impacted records have been remediated, and the business-impacting exception rate remains below the approved threshold for two monthly cycles. Evidence from production control reports across both cycles is stronger than a single test, a stakeholder sign-off, or a one-time cleansing result because it demonstrates sustained fitness for purpose after remediation. The key distinction is between proving that a fix was implemented and proving that the defect is controlled in normal operation.

• Development testing confirms rule behavior before or outside full operation, but it does not prove sustained production performance.
• User satisfaction may support acceptance, but it does not verify the source correction, remediated records, or threshold results.
• One-time profiling can show cleanup success at a point in time, but it does not demonstrate two-cycle monitoring or source-process control.

Question 2

Topic: Root Cause Analysis and Remediation

A retailer finds that 14% of new customer records have invalid province codes. The defect starts in the web registration form, which accepts free-text province values. Incorrect codes cause failed tax calculations in the billing system, and the same defect reappears after each weekly warehouse cleansing cycle. The customer data steward owns the approved province reference list and quality rule. Which remediation approach is the best quality decision?

Options:

• A. Continue weekly warehouse cleansing and add a dashboard trend

• B. Ask billing users to manually correct invalid province codes

• C. Enforce the steward-approved reference list at capture and remediate existing records

• D. Relax the province-code rule to accept common spelling variants

Best answer: C

Explanation: Effective remediation should address the cause of the defect, not only its symptoms. Here, the invalid values originate at data capture because the registration form allows free text instead of the approved reference values. Since the defect affects tax calculation and recurs after downstream cleansing, sustainable remediation should place validation as close to the source as practical, use the steward-owned reference list and rule, and correct the existing invalid records so current billing risk is reduced. A dashboard may help monitor progress, but monitoring alone does not prevent recurrence. Manual downstream correction shifts effort to impacted users and leaves the weak capture control in place. Relaxing the rule would reduce reported exceptions without improving fitness for purpose.

• Warehouse-only cleansing treats repeated symptoms after data has already flowed downstream, so recurrence risk remains high.
• Manual billing correction may reduce immediate failures but assigns quality work to downstream users rather than fixing capture.
• Relaxed validation can hide exceptions, but tax calculation still requires standardized, approved province codes.

Question 3

Topic: Root Cause Analysis and Remediation

A data quality rule requires every commercial customer record sent to billing to have a validated tax registration ID. Profiling shows a 3% failure rate from one onboarding channel. Billing can still invoice these customers, but tax reporting needs the IDs before quarter-end. The onboarding product owner says a source-system fix is scheduled in 30 days. What is the best exception-handling action?

Options:

• A. Cleanse the missing IDs only in the billing dataset

• B. Escalate immediately as a critical governance breach

• C. Accept the defect as a permanent business tolerance

• D. Approve a time-bound exception with monitoring and an owner

Best answer: D

Explanation: Exception handling should match business impact, urgency, and the likelihood of sustainable correction. Here the defect is real, but billing can continue and the source-system fix is already planned. Because tax reporting still depends on resolution before quarter-end, the defect should not be ignored or permanently accepted. A time-bound exception records the temporary tolerance, accountable owner, expiry date, monitoring requirement, and remediation dependency. This keeps the issue visible while allowing operations to continue safely.

The key distinction is temporary risk acceptance with control evidence versus either over-escalating a managed defect or masking it downstream.

• Permanent acceptance fails because quarter-end tax reporting still requires the missing IDs.
• Immediate escalation is excessive because the impact is tolerable short term and a source fix is scheduled.
• Downstream cleansing may reduce billing symptoms but does not control or correct the onboarding source defect.

Question 4

Topic: Root Cause Analysis and Remediation

A customer master remediation project corrected 18,000 duplicate current records, and the latest batch load contains no duplicate customer IDs. The same integration mapping that caused the duplicates was changed last week. The data steward is asked whether the issue can be closed as a sustained improvement. What is the best closure evidence?

Options:

• A. Schedule recurring cleansing of duplicate records after each load

• B. Document the number of corrected records in the issue log

• C. Approve closure after the corrected records pass uniqueness checks

• D. Track the revised mapping with duplicate-rate monitoring across future loads

Best answer: D

Explanation: Remediation validation should distinguish record correction from process improvement. The corrected customer records and the clean latest load show that the immediate defect was addressed, but they do not yet prove that the root cause is controlled. Because the duplicate problem came from an integration mapping, closure as a sustained improvement should include evidence that the mapping change is in place and that a quality control monitors duplicate rates in subsequent loads against an agreed threshold. That evidence demonstrates both remediation effectiveness and ongoing prevention. One-time cleansing or a count of repaired records can support the remediation history, but neither proves control effectiveness.

• Current-record pass confirms the repaired data state but does not show that the changed process will keep preventing duplicates.
• Recurring cleansing treats symptoms after loading rather than validating that the root cause has been corrected.
• Issue-log count records activity volume, not whether the control is effective over time.

Question 5

Topic: Root Cause Analysis and Remediation

A bank’s customer risk scorecard shows a sudden rise in records failing the “occupation is required” rule. The failures affect regulatory reporting, but downstream analysts can still impute an occupation from free-text notes. Profiling shows the missing-rate increase began after a new digital onboarding release. The business steward says some new customer types may legitimately have no occupation. What is the best quality decision before selecting a remediation approach?

Options:

• A. Apply downstream imputation immediately for all failed records

• B. Open a source-system defect for the onboarding team

• C. Trace failed records through onboarding, mappings, rule definition, and steward-approved exceptions

• D. Ask the steward to relax the completeness threshold

Best answer: C

Explanation: Root-cause analysis should precede the choice of remediation. The facts point to several plausible causes: a new onboarding release may have stopped capturing occupation, an integration mapping may be dropping it, the rule may not reflect legitimate exceptions, or stewardship guidance may be incomplete. Because the data supports regulatory reporting, a quick downstream fix alone does not address sustained prevention. The right next step is to gather lineage, profiling, rule-definition, and exception evidence so the response can be matched to the cause: source-process correction, rule revision, stewardship clarification, or temporary downstream cleanup. The key takeaway is to avoid committing to a remediation path until the evidence separates the defect from the business rule and process context.

• Downstream imputation may reduce reporting pain, but it does not establish whether the defect comes from capture, mapping, rule design, or valid exceptions.
• Relaxing the threshold assumes the rule is wrong before confirming whether the missing values are legitimate or caused by the new release.
• Opening a source defect is plausible because timing matches the release, but the evidence is not sufficient to exclude mapping or rule-definition causes.

Question 6

Topic: Root Cause Analysis and Remediation

A data quality defect was opened because active business customer records were missing a valid tax identifier. The approved remediation added source-system validation and backfilled the affected records. The closure criterion is: remediated records have no open exceptions, and two consecutive daily loads stay below the 0.5% exception threshold.

Which evidence best supports closing the defect?

Options:

• A. Post-remediation rule results for the backfill and two daily loads

• B. A deployment note for the new source-system validation

• C. A monthly scorecard showing overall customer data improved

• D. A steward email confirming the remediation was completed

Best answer: A

Explanation: Closure evidence should prove that the agreed quality rule and closure criteria have been met, not merely that work was performed. In this scenario, the decisive evidence is a post-remediation validation result that covers both parts of the criterion: the backfilled records have no open exceptions, and two consecutive daily loads are below the approved exception threshold. That evidence ties remediation to measured fitness for purpose and supports sustainable defect closure. Implementation notes, confirmations, and broad scorecards may support status reporting, but they do not by themselves prove the defect condition has been resolved according to the agreed rule.

• Deployment evidence shows a control was implemented, but not whether the corrected and new data meet the rule.
• Completion confirmation records activity, but it lacks measured validation against the closure criterion.
• Overall scorecard improvement is too aggregated to prove this specific defect is resolved.

Question 7

Topic: Root Cause Analysis and Remediation

A data quality monitor detects that 8% of new invoice records are missing tax_jurisdiction, above the 0.5% threshold. The defect has been logged, triaged as high impact because a regulatory report depends on the field, and assigned to the billing data steward. Profiling shows the issue began when a new e-commerce feed was added. Which quality decision best moves the defect through the lifecycle?

Options:

• A. Close the defect because a steward has accepted ownership

• B. Clean only the reporting table and leave the feed unchanged

• C. Suppress the exceptions until the regulatory report is submitted

• D. Investigate the feed mapping, remediate the source, validate results, then close with evidence

Best answer: D

Explanation: A managed defect lifecycle moves from detection and logging into triage, ownership, investigation, remediation, validation, and closure. In this case, monitoring found the defect, it was logged, impact was assessed, and ownership was assigned. The profiling evidence points to a likely source-process cause: the new e-commerce feed. The appropriate quality response is to investigate that source mapping, correct the source or ingestion process, repair affected records as needed, rerun the quality rule, and close only when validation evidence shows the threshold is met. Closure is not just an administrative status; it should confirm that the business-impacting defect has been resolved and controlled.

• Ownership alone does not resolve or validate the defect; it only clarifies accountability for the next steps.
• Suppressing exceptions hides a high-impact regulatory issue and bypasses investigation and remediation.
• Reporting-only cleanup may mask symptoms downstream but leaves the source-process cause active.

Question 8

Topic: Root Cause Analysis and Remediation

A customer data remediation effort reduced monthly address-validation defects from 18,000 to 1,200, meeting the technical scorecard threshold. However, sales users still report failed territory assignments for several large accounts because addresses pass format checks but contain outdated branch locations. What is the best closure decision?

Options:

• A. Close the issue because the scorecard threshold was met

• B. Lower the validation threshold to capture more address defects

• C. Keep the issue open and validate against business-use failures

• D. Close the issue and open a separate training request

Best answer: C

Explanation: Remediation closure requires evidence that the defect is resolved for the intended business use. A reduced exception count is useful, but it is not sufficient when users still experience quality failures tied to the same issue. In this case, format-valid addresses still fail territory assignment because the content is stale. The closure decision should keep the issue open, investigate the reported failures, and update validation criteria or quality rules with the responsible steward and business users. The key distinction is between meeting a technical threshold and proving business fitness for purpose.

• Threshold-only closure fails because the visible user failures show the scorecard metric is not measuring the full business impact.
• Training request misclassifies a data-content problem as user behavior without resolving stale branch locations.
• Lowering the threshold changes measurement sensitivity but does not validate whether the remediation fixed territory assignment failures.

Question 9

Topic: Root Cause Analysis and Remediation

A retailer’s customer analytics team cleans duplicate customer records every month before producing churn reports. Profiling shows the duplicate rate returns to about 8% after each cleanup, mainly for accounts created through the mobile sign-up process. The churn model and campaign suppression rules both use this customer file, and the data stewardship group has limited capacity for manual review. Which action is the best quality decision?

Options:

• A. Increase monthly manual deduplication before churn reporting

• B. Exclude mobile sign-up records from churn reporting

• C. Publish a duplicate-rate scorecard without remediation

• D. Analyze and correct the mobile sign-up creation process

Best answer: D

Explanation: Sustainable data quality improvement focuses on root-cause analysis and remediation, not repeated downstream correction. The evidence shows a recurring uniqueness defect that reappears after each cleanup and is concentrated in one source process: mobile sign-up. Because the same customer file supports multiple downstream uses, repeated deduplication treats only the symptom and consumes scarce stewardship capacity. The better response is to investigate how mobile records are created, identify the process or rule gap, and implement a preventive control at the point of capture or integration. Monitoring can then confirm whether the duplicate rate stays reduced. Downstream cleanup may still be needed temporarily, but it should not be the main long-term control.

• More cleanup leaves the mobile sign-up defect in place, so the duplicate rate is likely to recur.
• Excluding records avoids some bad data but harms completeness and does not address the cause.
• Scorecard only improves visibility, but measurement without remediation will not prevent the recurring defect.

Question 10

Topic: Root Cause Analysis and Remediation

A customer master data quality rule flags records missing a verified tax identifier. Over the past year, the exception list has grown to 18,000 records. Many exceptions have no documented business rationale, no named owner, no expiration date, and no compensating control, but downstream reporting teams have learned to ignore them. What is the best response?

Options:

• A. Suppress the rule until the backlog is manually cleared

• B. Create a governed exception register with required approvals and reviews

• C. Archive exceptions older than 90 days from the dashboard

• D. Ask reporting teams to document why they ignore the exceptions

Best answer: B

Explanation: Exceptions are acceptable only when they are explicitly justified, owned, controlled, and periodically reviewed. In data quality management, an exception should not become a silent alternative to remediation. A governed exception register should capture the affected rule, business rationale, approving steward or owner, expiration or review date, impact, compensating control, and escalation path. This turns exception handling into part of the defect lifecycle rather than an unmanaged backlog. Suppression, archiving, or informal workarounds may reduce visible noise, but they do not address accountability or risk. The key is to distinguish approved, temporary exceptions from unresolved defects that require remediation or governance escalation.

• Rule suppression hides the control failure and weakens monitoring instead of managing the exception lifecycle.
• Dashboard archiving changes visibility but does not establish rationale, ownership, expiry, or controls.
• Reporting workarounds document local behavior after the fact but do not create governed approval or remediation accountability.

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