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Dama CDMP-RMD Exam (page: 3)
Dama Reference And Master Data Management
Updated on: 25-Dec-2025

Viewing Page 3 of 21
CDMP-RMD PDF 100 Questions

Master Data is similar to a physical product produced and sold by a company except for which of the following characteristics?

  1. Unavailability may impact the business
  2. Must fit the consumers' required use
  3. Need for information about its characteristics
  4. Depletes when pulled from inventory
  5. Has a useful life span

Answer(s): D

Explanation:

Master Data, similar to a physical product, must meet certain requirements such as fitting consumers' needs, needing information about its characteristics, impacting business when unavailable, and having a useful lifespan. However, unlike physical products, Master Data does not deplete when pulled from inventory. Master Data remains available for use even after being accessed multiple times, as it is digital information that can be replicated and shared without loss.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.
"Master Data Management and Data Governance" by Alex Berson and Larry Dubov.



Which of the following Is a characteristic of a probabilistic matching algorithm?

  1. A score is assigned based on weight and degree of match
  2. Each variable to be matched is assigned a weight based on its discriminating power
  3. Individual attribute matching scores arc used to create a match probability percentage.
  4. All answers are correct
  5. Following the matching process there are typically records requiring manual review and decisioning.

Answer(s): D

Explanation:

Probabilistic matching algorithms assign a score based on the weight and degree of match, assign weights to variables based on their discriminating power, and use individual attribute matching scores to create a match probability percentage. Additionally, after the matching process, some records typically require manual review and decisioning to ensure accuracy. Therefore, all provided characteristics describe the nature of probabilistic matching algorithms accurately.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.
"Master Data Management and Data Governance" by Alex Berson and Larry Dubov



The ISO definition of Master Data quality is which of the following?

  1. Data meets the objective dimensions but not the subjective dimensions
  2. Data meets all common requirements of all data users
  3. Data is compliant to all international, country, and industry standards
  4. The degree to which the data's characteristics fulfill individual users' requirements
  5. Identifies the company that created and owns the Master Data

Answer(s): D

Explanation:

The ISO definition of Master Data quality focuses on the degree to which the data's characteristics meet the requirements of individual users. This implies that quality is subjective and depends on whether the data is suitable and adequate for its intended purpose, fulfilling the specific needs of its users.


Reference:

ISO 8000-8:2015 - Data quality -- Part 8: Information and data quality: Concepts and measuring. DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 13: Data Quality Management.



Where is the most time/energy typically spent tor any MDM effort?

  1. Subscribing content from the MDM environment
  2. Designing the Enterprise Data Model
  3. Vetting of business entities and data attributes by Data Governance process
  4. Publishing content to the MDM environment
  5. Securing funding for the MDM effort

Answer(s): C

Explanation:

In any Master Data Management (MDM) effort, the most time and energy are typically spent on vetting business entities and data attributes through the Data Governance process. This step ensures that the data is accurate, consistent, and adheres to defined standards and policies. It involves significant collaboration and decision-making among stakeholders to validate and approve the data elements to be managed.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.
"Master Data Management and Data Governance" by Alex Berson and Larry Dubov.



Can Reference data be used for financial trading?

  1. No because customer data is not considered reference data
  2. No. reference data is static, financial data trading is dynamic
  3. No. since financial trades change every second they cannot use reference data
  4. Yes. but only less than 1096 can be used
  5. Yes. an estimated 70% of data being used in financial transactions is reference data

Answer(s): E

Explanation:

Reference data plays a crucial role in financial trading. It includes data such as financial instrument identifiers, market data, currency codes, and regulatory classifications. Despite the dynamic nature of financial trades, reference data provides the necessary static information to execute and settle transactions. Industry estimates suggest that approximately 70% of the data used in financial transactions is reference data, underscoring its importance in the financial sector.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.
"The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball and Margy Ross.
Industry publications and whitepapers on reference data management in financial services.



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