Free CDMP-RMD Exam Braindumps
Reference And Master Data Management Questions 31–35 (page: 8)

Updated On: 10-Feb-2026

MOM Harmonization ensures that the data changes of one application:

  1. Are synchronized with all other applications who depend on that data
  2. Are recorded in the repository or data dictionary
  3. Agree with the overall MDM architecture
  4. include changes to the configuration of the database as well as the data
  5. Has a data steward to preview the data for quality

Answer(s): A

Explanation:

Master Data Management (MDM) Harmonization ensures that the data changes of one application are synchronized with all other applications that depend on that data. MDM Harmonization Definition: This process involves aligning and reconciling data from different sources to ensure consistency and accuracy across the enterprise. Synchronization: Ensuring that changes in one application are reflected across all dependent applications prevents data inconsistencies and maintains data integrity.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
CDMP Study Guide



MDM matching algorithms benefit from all of the following data characteristics except for which of the following?

  1. Distinctiveness across the population of data
  2. Low number of common data points
  3. High level of comparability of the data elements
  4. Structural heterogeneity of data elements
  5. High validity of the data

Answer(s): D

Explanation:

MDM matching algorithms benefit from various data characteristics but do not benefit from "Structural heterogeneity of data elements."
Matching Algorithms: These are used in MDM to identify and link data records that refer to the same entity across different systems.
Data Characteristics:
Distinctiveness: Helps in accurately matching records.

Common Data Points: Aids in the comparison process.
Comparability: Facilitates effective matching.
Validity: Ensures the data is accurate and reliable.
Structural Heterogeneity: Different structures can complicate the matching process, making it harder to align data.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
CDMP Study Guide



The following are examples of entities for which you need to manage master data:

  1. Employee Assignment. Employer. Transaction
  2. Party, Account Balance, Order
  3. Customer, Transaction, Product
  4. Customer, Product, Employee
  5. Product, Order, Inventory

Answer(s): D

Explanation:

Entities such as Customer, Product, and Employee are typical examples of master data that need to be managed.
Master Data Entities: These are the key data objects around which business transactions are conducted.
Examples:
Customer: Central to sales and service operations.
Product: Essential for inventory and sales management.
Employee: Critical for HR and payroll systems.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
CDMP Study Guide



_____ are a primary supplier of master data content to a MDM program.

  1. Configuration management database (CMDB)
  2. Systems of record
  3. Business intelligence applications
  4. Data catalog
  5. Point of sale systems

Answer(s): B

Explanation:

Systems of record are primary suppliers of master data content to an MDM program. Systems of Record: These are authoritative data sources that provide consistent and reliable master data.
Role in MDM: They supply accurate and up-to-date master data, ensuring that the MDM system has a solid foundation of information.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
CDMP Study Guide



What data architecture component is typically used for ingesting raw source system data?

  1. Integration Zone
  2. Landing Zone
  3. Curation Zone
  4. Presentation Zone
  5. Analytics Zone

Answer(s): B

Explanation:

The Landing Zone is typically used for ingesting raw source system data. Data Architecture Component: The landing zone is where raw data from various source systems is initially collected and stored.
Function: It acts as a staging area before the data undergoes further processing, transformation, or analysis.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
CDMP Study Guide



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