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DAMA CDMP-RMD Exam Syllabus Topics:

Topic	Details
Topic 1	Reference Data Management (RDM) Lifecycle: The lifecycle of reference data management is covered in this topic.
Topic 2	Fundamentals of Reference and Master Data: The fundamental ideas of reference and master data are covered in this section, along with their definitions, distinctions, and significance in data management.
Topic 3	Master Data Management (MDM) Lifecycle: The phases of the MDM lifecycle such as planning, design, implementation, and continuous operation are covered in this section.
Topic 4	Data Architecture: The design and implementation of data architecture for reference and master data are covered in detail in this topic. It addresses concepts including integration, standardization, and data modeling.
Topic 5	Data Stewardship: The management of reference and master data by data stewards is the focal point of this topic. It addresses concepts such as accuracy, consistency, and quality of data.
Topic 6	MDM and RDM Tools and Technologies: The technologies and tools available for managing reference and master data are discussed in this section.
Topic 7	Data Governance: The function of data governance in reference and master data management is examined in this section. It addresses policies, accountability, and data ownership.

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DAMA Reference And Master Data Management Exam Sample Questions (Q79-Q84):

NEW QUESTION # 79
The 3 primary categories of components in a MDM framework are:

A. Matching, linking. & verification
B. Program, project, task
C. Integration, quality, & governance
D. People, process, & technology
E. Structure, ETL, & storage

Answer: D

Explanation:
The three primary categories of components in a Master Data Management (MDM) framework are people, process, and technology. Here's a detailed breakdown:
* People:
* Roles and Responsibilities: Involves defining roles such as data stewards, data owners, and data governance committees who are responsible for managing and overseeing master data.
* Skills and Training: Ensuring that the individuals involved have the necessary skills and training to manage master data effectively.
* Process:
* Data Governance: Establishing policies, procedures, and standards for managing master data to ensure its accuracy, consistency, and reliability.
* Data Lifecycle Management: Processes for creating, maintaining, and retiring master data.
* Technology:
* MDM Tools and Platforms: Utilizing technology solutions to support the management of master data, including data integration, data quality, and data management platforms.
* Infrastructure: Ensuring the necessary technical infrastructure is in place to support MDM
* activities.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 80
The ISO definition of Master Data quality is which of the following?

A. The degree to which the data's characteristics fulfill individual users' requirements
B. Identifies the company that created and owns the Master Data
C. Data meets all common requirements of all data users
D. Data is compliant to all international, country, and industry standards
E. Data meets the objective dimensions but not the subjective dimensions

Answer: A

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.
References:
* 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.

NEW QUESTION # 81
Every process within a MDM framework includes:

A. Automation of all process tasks
B. A degree of governance
C. A separate data steward
D. Data enrichment
E. Reference data

Answer: B

Explanation:
Every process within an MDM framework includes a degree of governance. Here's why:
* Governance Definition:
* Policies and Standards: Governance involves the establishment of policies, standards, and procedures to ensure data quality, consistency, and compliance.
* Oversight: Provides oversight and accountability for data management practices.
* MDM Processes:
* Inherent Governance: All MDM processes, from data integration to data quality management, incorporate governance to ensure the integrity and reliability of master data.
* Data Stewardship: Involves data stewards who oversee data governance activities, ensuring adherence to established standards and policies.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 82
Master and Reference Data are forms of:

A. Data Quality
B. Data Architecture
C. Data Mapping
D. Data Integration
E. Data Security

Answer: B

Explanation:
Master and Reference Data are forms of Data Architecture. Here's why:
* Data Architecture Definition:
* Structure and Design: Data architecture involves the structure and design of data systems, including how data is organized, stored, and accessed.
* Components: Encompasses various components, including data models, data management processes, and data governance frameworks.
* Role of Master and Reference Data:
* Core Components: Master and Reference Data are integral components of an organization's data architecture, providing foundational data elements used across multiple systems and processes.
* Organization and Integration: They play a critical role in organizing and integrating data, ensuring consistency and accuracy.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 83
What characteristics does Reference data have that distinguish it from Master Data?

A. It is less volatile, less complex, and typically smaller than Master Data sets
B. It is always data from an outside source such as a governing body
C. It is more volatile and needs to be highly structured
D. It always has foreign database keys to link it to other data
E. It provides data for transactions

Answer: D

Explanation:
Reference data and master data are distinct in several key characteristics. Here's a detailed explanation:
* Reference Data Characteristics:
* Stability: Reference data is generally less volatile and changes less frequently compared to master data.
* Complexity: It is less complex, often consisting of simple lists or codes (e.g., country codes, currency codes).
* Size: Reference data sets are typically smaller in size than master data sets.
* Master Data Characteristics:
* Volatility: Master data can be more volatile, with frequent updates (e.g., customer addresses, product details).
* Complexity: More complex structures and relationships, involving multiple attributes and entities.
* Size: Larger in size due to the detailed information and numerous entities it encompasses.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 7: Master Data Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"

NEW QUESTION # 84
......

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CDMP-RMD RELIABLE TEST SIMULATOR | LATEST CDMP-RMD EXAM TOPICS

CDMP-RMD Reliable Test Simulator | Latest CDMP-RMD Exam Topics