CDMP-RMD FLEXIBLE LEARNING MODE & VALID CDMP-RMD EXAM PATTERN

CDMP-RMD Flexible Learning Mode & Valid CDMP-RMD Exam Pattern

CDMP-RMD Flexible Learning Mode & Valid CDMP-RMD Exam Pattern

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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
  • 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
  • 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 4
  • 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 5
  • 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 6
  • 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 7
  • MDM and RDM Tools and Technologies: The technologies and tools available for managing reference and master data are discussed in this section.

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DAMA Reference And Master Data Management Exam Sample Questions (Q61-Q66):

NEW QUESTION # 61
What is a trait of a Consolidated style MDM approach?

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

Answer: C

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 # 62
What is a Canonical Data Model?

  • A. Used in a transactional operating environment
  • B. Used for data replication
  • C. A common data modelwhich standardizes the format in which data will be shared
  • D. Data that is not used frequently is moved to the Canonical model
  • E. An alternate data structure which is less costly to the organization

Answer: C

Explanation:
A Canonical Data Model (CDM) is a design pattern used in data integration and exchange to create a standardized format for data that will be shared across different systems.
* Canonical Data Model Definition:
* A CDM provides a common, consistent, and agreed-upon representation of data across different systems within an organization.
* It serves as an intermediary format to simplify data exchange and integration.
* Standardization:
* The primary purpose of a CDM is to standardize the format of data. This ensures that data from different sources can be integrated, understood, and used without needing extensive transformation or reformatting.
* It addresses the problem of data heterogeneity, where different systems may have their own data formats and structures.
* Data Integration:
* By using a CDM, organizations can facilitate easier and more efficient data integration processes.
Data from various systems can be mapped to the canonical model, enabling seamless data exchange and interoperability.
* It simplifies the maintenance and management of data integration solutions by providing a single, unified data model.
* Use Cases:
* CDMs are commonly used in enterprise application integration (EAI), service-oriented architectures (SOA), and other environments where data needs to be exchanged between multiple systems.


NEW QUESTION # 63
Depending on the granularity and complexity of what the Reference Data represents. it may be structured as a simple list, a cross-reference or a taxonomy.

  • A. True
  • B. False

Answer: A

Explanation:
Reference data can be structured in various ways depending on its granularity and complexity.
* Simple List:
* Reference data can be a simple list when it involves basic, discrete values such as country codes or product categories.
* Cross-Reference:
* When reference data needs to map values between different systems or standards, it can be structured as cross-references. For example, mapping old product codes to new ones.
* Taxonomy:
* For more complex hierarchical relationships, reference data can be structured as a taxonomy. This involves categorizing data into parent-child relationships, like an organizational hierarchy or biological classification.


NEW QUESTION # 64
Which of the following is true about MDM?

  • A. Once master data is published by a MDM hub. it no longer is considered master ' data
  • B. Manages master data formally with a high degree of diligence and collaboration
  • C. A MDMprogram must include a MDM software application
  • D. MDM programs have a definitive life span
  • E. Master data is not managed without a formal MDM program

Answer: B

Explanation:
MDM (Master Data Management) is characterized by formal management with a high degree of diligence and collaboration. Here's why:
* Formal Management:
* Structured Processes: MDM involves structured processes for managing master data, including data governance, data quality management, and data stewardship.
* Policies and Standards: Establishes and enforces policies and standards to ensure data consistency, accuracy, and integrity.
* Collaboration:
* Cross-Functional Teams: Requires collaboration across different departments, including IT, business units, and data governance teams.
* Stakeholder Involvement: Engages various stakeholders in the data management process, ensuring that master data meets the needs of the entire organization.
* 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 # 65
What characteristics does Reference data have that distinguish it from Master Data?

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

Answer: C

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 # 66
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