CDMP-RMD EXAM TORRENTS: REFERENCE AND MASTER DATA MANAGEMENT EXAM PREPARE TORRENTS & CDMP-RMD TEST BRAINDUMPS

CDMP-RMD Exam Torrents: Reference And Master Data Management Exam Prepare Torrents & CDMP-RMD Test Braindumps

CDMP-RMD Exam Torrents: Reference And Master Data Management Exam Prepare Torrents & CDMP-RMD Test Braindumps

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DAMA CDMP-RMD Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • Reference Data Management (RDM) Lifecycle: The lifecycle of reference data management is covered in this topic.
Topic 3
  • 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.
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.

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DAMA Reference And Master Data Management Exam Sample Questions (Q11-Q16):

NEW QUESTION # 11
What technology option can provide better support of a Registry style MDM?

  • A. Columnar database
  • B. Complex queries
  • C. Data virtualization
  • D. JSON mapping
  • E. ETL toolset

Answer: C

Explanation:
Registry style MDM involves maintaining a central registry that stores references to master data while allowing the actual data to remain in the source systems. This approach requires technologies that support data integration and real-time access without physically moving the data.
* JSON Mapping:
* JSON mapping is useful for data exchange but does not specifically support the registry style MDM approach.
* ETL Toolset:
* ETL (Extract, Transform, Load) tools are typically used for batch data processing and integration, which may not align with the real-time data access requirements of a registry style MDM.
* Columnar Database:
* Columnar databases are optimized for analytical queries but are not specifically designed for supporting registry style MDM.
* Complex Queries:
* While complex queries can be part of the data access strategy, they are not a comprehensive solution for registry style MDM.
* Data Virtualization:
* Data virtualization provides a unified view of data from multiple sources without physically moving the data. It supports real-time data access and integration, making it well-suited for registry style MDM.
* It enables organizations to access and manage master data across different systems while maintaining a central registry for reference.


NEW QUESTION # 12
What is a trait of a Consolidated style MDM approach?

  • A. System of record
  • B. Complex queries
  • C. None of these
  • D. Access by index
  • E. Data latency

Answer: A

Explanation:
In a Consolidated style MDM (Master Data Management) approach, data from multiple source systems is integrated into a single consolidated repository. This consolidated repository acts as the authoritative source for master data, often referred to as the "system of record." The system of record maintains the most accurate, up-to-date, and comprehensive view of master data. Key traits of this approach include:
* Centralization: All master data is centralized in one repository, which simplifies data management and governance.
* Consistency: Ensures that all users and systems access the same consistent set of master data.
* Data Quality: Enhances data quality through data cleansing, deduplication, and validation processes.
* Single Source of Truth: Serves as the definitive source for master data, reducing discrepancies and inconsistencies across the organization.
References:
* DAMA-DMBOK: Data Management Body of Knowledge, 2nd Edition.
* "Master Data Management and Data Governance" by Alex Berson and Larry Dubov.


NEW QUESTION # 13
The MDM program's governance scope should include:

  • A. Internal data subscribers to the master data
  • B. Data sources of the master data Q All of the above
  • C. External third parties using Master Data
  • D. Master Data authored in the MDM user interface

Answer: B

Explanation:
The governance scope of an MDM program should be comprehensive, encompassing all aspects and stakeholders involved in the management and usage of master data.
* Internal Data Subscribers to the Master Data:
* Internal users and systems that consume master data must be governed to ensure they have access to accurate and consistent data.
* Master Data Authored in the MDM User Interface:
* Governance should include the processes and controls around how master data is created and maintained through the MDM interface.
* External Third Parties Using Master Data:
* External parties that use or access master data must be governed to ensure data security, privacy, and compliance with regulations.
* Data Sources of the Master Data:
* The sources from which master data is derived must be governed to ensure data quality, integrity, and consistency.


NEW QUESTION # 14
For MDMs. what is meant by a classification scheme?

  • A. A way of classifying unstructured data
  • B. Codes that represent a controlled set of values
  • C. Descriptive language used to control objects
  • D. A vocabulary view covering a limited range of topics

Answer: B

Explanation:
In Master Data Management (MDM), a classification scheme refers to a structured way of organizing data by using codes that represent a controlled set of values. These codes help in categorizing and standardizing data, making it easier to manage, search, and analyze.
References:
* 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.


NEW QUESTION # 15
Every process within a MDM framework includes:

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

Answer: E

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 # 16
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