CDMP-RMD Demotesten - CDMP-RMD Zertifikatsfragen

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CDMP-RMD Zertifikatsfragen & CDMP-RMD Prüfungs-Guide

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DAMA CDMP-RMD Prüfungsplan:

Thema	Einzelheiten
Thema 1	Data Quality Management: The methods and procedures for guaranteeing the quality of reference and master data are examined in this topic. Moreover, it focuses on validation, monitoring, and data cleansing.
Thema 2	Master Data Management (MDM) Lifecycle: The phases of the MDM lifecycle such as planning, design, implementation, and continuous operation are covered in this section.
Thema 3	MDM and RDM Tools and Technologies: The technologies and tools available for managing reference and master data are discussed in this section.
Thema 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.
Thema 5	Reference Data Management (RDM) Lifecycle: The lifecycle of reference data management is covered in this topic.
Thema 6	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.

DAMA Reference And Master Data Management Exam CDMP-RMD Prüfungsfragen mit Lösungen (Q61-Q66):

61. Frage
When establishing a MOM. what is the benefit of doing data profiling?

A. Develop batch data flows for a scheduler
B. Manage the design of the data warehouse
C. Analyze data values and see how closely they correspond to a defined set of valid values
D. Develop services to access, transform and deliver data
E. Develop data migration approach

Antwort: C

Begründung:
* Definitions and Context:
* Data Profiling: This is the process of examining data from existing data sources and collecting statistics or informative summaries about that data.
* Master Data Management (MDM): Establishing MDM involves processes and technologies for
* managing the non-transactional data entities of an organization.
* Explanation:
* Data profiling helps to understand the data's characteristics and quality by analyzing data values and comparing them to defined valid values.
* This process is crucial in establishing a Master Data Management (MDM) system as it ensures the data adheres to the defined standards and is clean, accurate, and ready for integration into the MDM system.
References:
* DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition, Chapter 11: Master and Reference Data Management.
* Kimball, R. & Caserta, J. (2004). The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data.

62. Frage
Master and Reference Data are forms of:

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

Antwort: B

Begründung:
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)"

63. Frage
A division of power approach to master data governance provides the benefit of:

A. Facilitating a decision by committee model
B. Spreads the blame for bad decisions
C. Lower expense
D. Centralizing responsibility
E. Better alignment of decisions based on varying levels of organizational data sharing

Antwort: E

Begründung:
* Division of Power in Data Governance:This approach distributes decision-making authority across different levels or areas within the organization.
* Benefits:
* Better alignment of decisions:By distributing power, decisions can be made that are better suited to the specific needs and contexts of different parts of the organization. This ensures that decisions about data management are relevant and effective for each particular area.
* Avoids centralization issues:Centralized decision-making can often be disconnected from the needs of different departments or functions.
* Improved responsiveness:
Decentralized governance can enable faster and more contextually appropriate responses to data management issues.
* Other Options Analysis:
* Spreads the blame for bad decisions:This is not a strategic benefit but rather a negative consequence.
* Centralizing responsibility:This contradicts the concept of division of power.
* Lower expense:While decentralization might lead to better decision-making, it doesn't inherently mean lower costs.
* Facilitating a decision by committee model:This can lead to slower decision-making processes and isn't the primary benefit of a division of power.
* Conclusion:The key benefit of a division of power approach in master data governance is the better alignment of decisions based on varying levels of organizational data sharing.
References:
* DMBOK Guide, sections on Data Governance and Organizational Structures.
* CDMP Examination Study Materials.

64. Frage
Reference and Master data ran be stored in separate repositories:

A. True
B. False

Antwort: A

Begründung:
Reference data and master data serve different purposes within an organization, and storing them in separate repositories can be beneficial for managing them effectively.
* Reference Data:
* Reference data is used to classify or categorize other data. Examples include code tables, taxonomies, and standard lists like country codes or industry classifications.
* It is often less volatile and has a higher degree of standardization.
* Master Data:
* Master data refers to the core business entities that are essential for operations, such as customers, products, employees, and suppliers.
* It is often more dynamic and requires frequent updates to ensure accuracy and consistency across systems.
* Separate Repositories:
* Storing reference and master data in separate repositories allows for tailored management strategies, governance, and security measures suited to their specific needs.
* This approach can improve performance, data quality, and accessibility by reducing complexity and focusing resources on maintaining each type of data appropriately.

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

A. Trust Model Technologies
B. Static masking
C. Usage Agreements
D. Dynamic Masking
E. Encryption ciphers

Antwort: C

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

66. Frage
......

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CDMP-RMD Demotesten - CDMP-RMD Zertifikatsfragen

CDMP-RMD Zertifikatsfragen & CDMP-RMD Prüfungs-Guide

DAMA CDMP-RMD Prüfungsplan:

DAMA Reference And Master Data Management Exam CDMP-RMD Prüfungsfragen mit Lösungen (Q61-Q66):

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