Free DAMA CDMP Fundamentals Practice Questions: Master and Reference Data Management

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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: Master and Reference Data Management

A company has an MDM hub that matches and merges customer records each night. Duplicate and incomplete customer master records continue to reappear because the CRM and billing systems allow different teams to create customers without a common owner, approval step, or required attributes. Which remediation best fits the need?

Options:

• A. Lower the matching confidence threshold in the MDM hub

• B. Build a dashboard showing duplicate customer trends

• C. Assign stewardship and enforce source creation controls

• D. Increase the frequency of nightly survivorship processing

Best answer: C

Explanation: MDM governance addresses the business accountability and process controls needed to keep master data fit for use. Matching and survivorship can identify and consolidate duplicate records, but they do not remove the upstream cause when source applications allow uncontrolled creation of customer records. The durable remediation is to establish data ownership and stewardship for the customer domain, define creation and update standards, require key attributes, and implement approval or validation controls in the CRM and billing processes. Monitoring may still be useful, but prevention at the point of capture is the key control.

• Matching threshold may catch more potential duplicates, but it can also increase false matches and does not address missing ownership.
• More frequent survivorship cleans up symptoms faster, but duplicate creation will continue in the source systems.
• Trend reporting helps visibility and escalation, but reporting alone does not create accountability or process control.

Question 2

Topic: Master and Reference Data Management

A retailer maintains a shared product category code set used by order entry, supplier feeds, and BI reports. Teams currently email requested changes directly to database administrators, which has caused inactive categories to reappear and different systems to use different mappings. Which lifecycle control best addresses the need to prevent unauthorized changes, obsolete values, duplicated records, and inconsistent downstream use?

Options:

• A. Free-text category entry with periodic duplicate reports

• B. One-time cleanup to remove inactive category values

• C. Nightly replication of the category table to all systems

• D. Steward-approved change and version-controlled publication workflow

Best answer: D

Explanation: Reference data and master data need lifecycle controls that govern how values are proposed, approved, changed, published, deprecated, and retired. In this case, the problem is not only synchronization speed; it is uncontrolled change. A steward-approved workflow with version control and controlled publication prevents informal updates, preserves history, coordinates effective dates, and gives downstream systems a single authorized source for valid values. Cleanup and replication can support the process, but they do not replace governance over the lifecycle of the code set.

• Replication alone can spread the latest table faster, but it may also spread unauthorized or obsolete values.
• One-time cleanup fixes current defects but does not prevent future uncontrolled changes.
• Free-text entry increases variation and duplicate risk, even if duplicates are reviewed later.

Question 3

Topic: Master and Reference Data Management

A company is consolidating customer master records from CRM, billing, and support systems. The matching tool confidently groups likely duplicates, but several surviving-record conflicts remain, such as whether the “strategic account” flag from CRM should override the billing account status when the customer is under contract renewal. What is the best next step?

Options:

• A. Increase the matching confidence threshold

• B. Route the conflicts to business data stewards

• C. Accept the most recent source value

• D. Store all conflicting values as aliases

Best answer: B

Explanation: Automated matching is well suited to identifying likely duplicate master records using rules, probabilities, and confidence scores. It does not replace stewardship judgment when the conflict depends on business meaning, policy, or operational context. In this case, the issue is not whether records match; it is which value should survive when source systems disagree and the decision affects account treatment during contract renewal. A business data steward, guided by MDM governance rules and escalation paths, should resolve or escalate the conflict so the golden record reflects agreed business intent.

Changing match thresholds addresses duplicate identification, not survivorship policy. A simple recency rule or keeping every value can create inconsistent master data when business context matters.

• Threshold tuning helps with match precision and recall, but the tool has already grouped likely duplicates with confidence.
• Most recent value is a simplistic survivorship rule and may ignore authoritative source, contract status, or policy.
• Aliases for conflicts may preserve history, but they do not resolve the trusted value needed for the master record.

Question 4

Topic: Master and Reference Data Management

A bank is building a customer master. The same corporate customers appear in onboarding and loan systems with slightly different legal names and parent-company values. Matching by tax identifier finds likely duplicates, but data stewards need a controlled way to choose the trusted attributes and resolve uncertain matches. Which MDM control best fits this need?

Options:

• A. Match-and-merge rules with survivorship and steward review

• B. A data retention schedule for customer records

• C. A dashboard reconciliation report for customer counts

• D. A reference data code-set approval workflow

Best answer: A

Explanation: MDM governance uses matching, merging, survivorship, and stewardship controls to create and maintain trusted master data. In this case, the issue is not just reporting inconsistency; the organization has duplicate customer entities and conflicting master attributes across systems. Match rules identify records that may represent the same real-world customer. Merge and survivorship rules determine which attribute values become part of the trusted customer record. Steward review is appropriate when matches or attribute choices are uncertain and need business accountability. A report may reveal the problem, but it does not govern the resolution of duplicate entities or conflicting attributes.

• Code-set workflow fits reference data such as status codes or country lists, not duplicate customer master records.
• Reconciliation reporting can show count differences, but it does not create governed match, merge, or survivorship decisions.
• Retention scheduling manages how long records are kept, not which records represent the same customer.

Question 5

Topic: Master and Reference Data Management

A health insurer uses the same claim status values in claims processing, provider portals, analytics, and regulatory submissions. Teams currently add local status codes when workflows change, causing inconsistent reports and rejected submissions. The data governance council is new and wants a reusable control that limits disruption while recognizing that external reporting codes change periodically. What is the best professional decision?

Options:

• A. Create a claim master record with survivorship rules

• B. Document the status meanings only in the business glossary

• C. Let each application owner maintain local claim statuses

• D. Manage claim status as enterprise reference data with controlled code-set changes

Best answer: D

Explanation: Reference data consists of shared codes, classifications, and permissible values used to categorize or control other data. Claim status values are not the core business entity itself; they are a reusable code set used across operational, analytical, and regulatory processes. Because changes can affect integrations, reports, and submissions, they need named stewardship, versioned publication, approval workflow, impact assessment, and mappings where local or external codes differ. Master data management would be appropriate for core entities such as customer, provider, product, or claim parties, where identity resolution and survivorship are central. The key distinction is that reference data change control governs valid values, while master data management governs authoritative records about key business entities.

• Master record treatment fails because survivorship and identity resolution do not address controlled values for claim statuses.
• Local ownership fails because independent codes are already causing inconsistent reporting and rejected submissions.
• Glossary-only documentation fails because definitions do not provide approval, versioning, distribution, or mapping control.

Question 6

Topic: Master and Reference Data Management

A regional bank is launching a customer MDM capability. Customer records arrive from online banking, branch systems, and a loan platform. The business needs one trusted customer view, household hierarchies for relationship pricing, and controlled handling of conflicting phone numbers and privacy preferences. Match confidence varies, and the bank has named business stewards but limited automation. Which approach should the data management team take?

Options:

• A. Merge all records by newest update timestamp

• B. Keep source records separate and reconcile only in reports

• C. Use exact national identifier matching and auto-approve all merges

• D. Apply matching, survivorship rules, hierarchy management, and steward review

Best answer: D

Explanation: Master data management creates and maintains trusted, shared master data for key business entities such as customers. In this case, the bank needs more than duplicate detection. It needs matching to identify likely same-customer records, merging to consolidate them, survivorship rules to decide which source value is retained for each attribute, hierarchy management to represent household relationships, and stewardship review where confidence is low or conflicts affect governed data such as privacy preferences. Automation can improve consistency, but steward oversight is important when business risk and match uncertainty remain. A timestamp-only or exact-match-only approach is too narrow for a controlled MDM program.

• Newest timestamp fails because recency alone does not prove identity or determine the most authoritative value for each attribute.
• Report reconciliation leaves conflicting master records unresolved and shifts MDM work into downstream analytics.
• Exact identifier matching misses legitimate duplicates and auto-approval is risky when match confidence and privacy conflicts vary.

Question 7

Topic: Master and Reference Data Management

A retailer is implementing a customer master hub. Profiling shows likely duplicate customer records, conflicting phone and address values, and unclear household-to-individual relationships. Some duplicate candidates have low confidence scores and need business judgment before consolidation. Which MDM practice best fits this need?

Options:

• A. Let the newest source update overwrite all conflicting values

• B. Apply match rules, survivorship rules, hierarchy management, and steward review

• C. Load all source records unchanged into the reporting database

• D. Create a reference code list for customer status values

Best answer: B

Explanation: Master data management uses matching to identify records that may represent the same real-world party, merging to consolidate confirmed duplicates, and survivorship rules to decide which source or value becomes the trusted master value. Hierarchy management handles relationships such as household-to-individual, company-to-subsidiary, or customer-to-account. When match confidence is low or business rules are insufficient, data stewards review exceptions and make governed decisions rather than allowing blind automation. The key takeaway is that MDM is not just deduplication; it combines automated rules with stewardship and relationship management to produce trusted master data.

• Reference code lists manage allowed values such as statuses, but they do not resolve duplicate customer identities or conflicting attributes.
• Unchanged reporting loads preserve source differences and leave duplicate master records unresolved.
• Newest update wins is a weak survivorship shortcut because recency alone may not identify the most trusted value.

Question 8

Topic: Master and Reference Data Management

A retailer needs to introduce a new product category code for a campaign launching in two weeks. The category will be used by order management, the master data hub, and finance BI reports. Finance is concerned about margin reporting consistency, and the organization has an established reference data steward and product data owner. What is the BEST professional decision?

Options:

• A. Add the category directly in BI for the campaign deadline.

• B. Submit a governed change request with impact review and data owner approval.

• C. Use a temporary free-text category until the next quarterly review.

• D. Ask the database team to insert the code in production.

Best answer: B

Explanation: Reference data lifecycle management requires controlled approval for changes to shared code sets, especially when they affect operational systems and reporting. The new product category has cross-system use and finance reporting impact, so the change should not be made locally or treated as a purely technical update. A governed request should document the proposed code, definition, business justification, effective date, downstream impacts, mapping needs, and communication plan. The reference data steward can coordinate review, while the product data owner provides business approval. The two-week deadline may justify an expedited path, but not bypassing change control. The key is to protect consistency while enabling the business need.

• BI-only change creates reporting divergence because operational systems and the master data hub would not share the same approved code.
• Technical insertion treats the change as database maintenance, but the main risk is business meaning and cross-system impact.
• Free-text workaround weakens standardization and can create avoidable data quality defects before formal approval.

Question 9

Topic: Master and Reference Data Management

A customer MDM hub identifies two high-confidence duplicate customer records, but the records disagree on legal name, tax status, and preferred billing account. The match score is above the auto-merge threshold, yet the conflict could affect invoicing and regulatory reporting. What should the organization do next?

Options:

• A. Keep both records permanently as separate masters

• B. Auto-merge using the highest match score

• C. Ask database administrators to choose the newest record

• D. Route the conflict to a data steward for business review

Best answer: D

Explanation: Automated matching is useful for identifying likely duplicate master records by applying rules, probabilities, or thresholds. It does not by itself resolve every survivorship decision. When conflicting attributes have business, legal, regulatory, or customer-impact consequences, a data steward or accountable business role should review the conflict using approved policies and business context. The match engine can present evidence, candidate matches, confidence scores, and suggested survivorship outcomes, but stewardship judgment is needed where automated rules may create operational or compliance risk.

The key distinction is that matching detects and proposes; stewardship adjudicates exceptions that require business meaning and accountability.

• Highest score only fails because a match score supports duplicate detection but does not safely resolve sensitive attribute conflicts.
• Permanent separation fails because likely duplicates should be adjudicated, not ignored without review.
• Technical custody fails because database administrators manage platforms and data operations, not business survivorship decisions.

Question 10

Topic: Master and Reference Data Management

A company is building a single customer view from CRM, billing, and support. The feeds contain duplicate customers, conflicting names and addresses, different active/inactive statuses, and records that must be retired or reactivated. Leaders suggest a one-time integration job to copy the latest values into a table. Which response best distinguishes the master data concern?

Options:

• A. Metadata management needs catalog entries for each source field.

• B. Master data needs governed identity, survivorship, quality, and lifecycle rules.

• C. Reference data needs a centrally published customer status code list.

• D. Transactional data needs reconciliation of each customer order.

Best answer: B

Explanation: Master data represents core business entities, such as customers, products, suppliers, or locations, that are reused across many processes and systems. A golden record is not produced reliably by simply copying the latest source value. It requires governed definitions, stewardship accountability, match and merge rules, data quality controls, survivorship rules for conflicting attributes, and lifecycle rules for creation, change, retirement, and reactivation. These controls keep the shared entity consistent as sources and business processes continue to change.

A one-time integration can populate a table, but master data management keeps the trusted version controlled over time.

• Reference code focus is too narrow because status codes may be reference data, but the main issue is resolving shared customer identities.
• Cataloging fields supports understanding and lineage, but it does not decide which customer record survives or how duplicates are merged.
• Order reconciliation concerns transactional facts, while the scenario centers on the shared customer entity used across systems.

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