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Free CDMP-RMD Exam Braindumps (page: 3)

Page 2 of 26
PDF with 100 Questions

Information Governance is a concept that covers the 'what', how', and why' pertaining to the data assets of an organization. The 'what', 'how', and 'why' are respectively handled by the following functional areas:

  1. Data Management. Information Technology, and Compliance
  2. Customer Experience. Information Security, and data Governance
  3. Data Governance. Information Technology, and Customer Experience
  4. Data Governance. Information Security, and Compliance
  5. Data Management, Information Security, and Customer Experience

Answer(s): D

Explanation:

Information Governance involves managing and controlling the data assets of an organization, addressing the 'what', 'how', and 'why'.
'What' pertains to Data Governance, which defines policies and procedures for data management. 'How' relates to Information Security, ensuring that data is protected and secure. 'Why' is about Compliance, ensuring that data management practices meet legal and regulatory requirements.


Reference:

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 1: Data Governance.

"Information Governance: Concepts, Strategies, and Best Practices" by Robert F. Smallwood.



What is a registry as it applies to Master Data?

  1. An index that points to Master Data in the various systems of record
  2. Any data available during record creation
  3. Reconciled versions of an organization's systems
  4. A starling point for matching and linking new records
  5. A system to identify how data is used for transactions and analytics

Answer(s): A

Explanation:

A registry in the context of Master Data Management (MDM) is a centralized index that maintains pointers to master data located in various systems of record. This type of architecture is commonly referred to as a "registry" model and allows organizations to create a unified view of their master data without consolidating the actual data into a single repository. The registry acts as a directory, providing metadata and linkage information to the actual data sources.


Reference:

DAMA-DMBOK2 Guide: Chapter 10 ­ Master and Reference Data Management "Master Data Management: Creating a Single Source of Truth" by David Loshin



The concept of tracking the number of MDM subject areas and source system attributes Is referred to as:

  1. Publish and Subscribe
  2. Hub and Spoke
  3. Mapping and Integration
  4. Subject Area and Attribute
    Scope and Coverage

Answer(s): D

Explanation:

Tracking the number of MDM subject areas and source system attributes refers to defining the scope and coverage of the subject areas and attributes involved in an MDM initiative. This process includes identifying all the data entities (subject areas) and the specific attributes (data elements) within those entities that need to be managed across the organization. By establishing a clear scope and coverage, organizations can ensure that all relevant data is accounted for and appropriately managed.


Reference:

DAMA-DMBOK2 Guide: Chapter 10 ­ Master and Reference Data Management "Master Data Management and Data Governance" by Alex Berson, Larry Dubov



All of the following methods arc a moans to protect and secure master data In a production environment except for which of the following?

  1. Encryption ciphers
  2. Static masking
  3. Trust Model Technologies
  4. Usage Agreements
  5. Dynamic Masking

Answer(s): D

Explanation:

Protecting and securing master data in a production environment can be achieved through various methods. Encryption ciphers, static masking, trust model technologies, and dynamic masking are all techniques used to safeguard data. However, usage agreements, while important for data governance and legal compliance, are not a technical method for securing data in the same way that the other options are. Usage agreements define the terms under which data can be accessed and used, but they do not directly protect the data itself.


Reference:

DAMA-DMBOK2 Guide: Chapter 11 ­ Data Security Management "Data Masking: A Key Component of a Secure Data Management Strategy" by Anjali Kaushik






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