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Free CDMP-RMD Exam Braindumps (page: 4)

Page 3 of 26
PDF with 100 Questions

Managing master data elements can be performed at which of the following points?

  1. Third-party Provider (e.g. D&B)
  2. Enterprise
  3. Application Suite (e.g. ERP)
  4. All Answers are correct

Answer(s): D

Explanation:

Managing master data elements can be performed at multiple levels within an organization. This includes third-party providers such as Dun & Bradstreet (D&B) which can supply enriched and standardized master data. At the enterprise level, organizations manage master data centrally to ensure consistency and quality across all systems and processes. Within application suites such as ERP (Enterprise Resource Planning) systems, master data management ensures that data is consistent and accurate within and across different applications. Therefore, master data elements can be managed at all these points.


Reference:

DAMA-DMBOK2 Guide: Chapter 10 ­ Master and Reference Data Management "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball



Which of the following is a method of deterministic matching?

  1. Sorted Neighborhood
  2. Regional Frequency
  3. Editing Distance
  4. Phonetic
  5. Exact string match

Answer(s): E

Explanation:

Deterministic matching is a method of record linkage that relies on exact matching criteria. This means that records are considered a match if certain key fields (e.g., name, Social Security Number) have exactly the same values. Exact string match is a straightforward example of deterministic matching, where the strings in specific fields must be identical for a match to be declared. Other methods like sorted neighborhood, regional frequency, editing distance, and phonetic matching are probabilistic or heuristic approaches that allow for some degree of variation or error in the data.


Reference:

DAMA-DMBOK2 Guide: Chapter 10 ­ Master and Reference Data Management "Entity Resolution and Information Quality" by John R. Talburt



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






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