CDMP-RMD REAL DUMPS, TRAINING CDMP-RMD TOOLS

CDMP-RMD Real Dumps, Training CDMP-RMD Tools

CDMP-RMD Real Dumps, Training CDMP-RMD Tools

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DAMA Reference And Master Data Management Exam Sample Questions (Q72-Q77):

NEW QUESTION # 72
Which is NOT considered a type of Master Data relationship?

  • A. Fixed-Level Hierarchy
  • B. Grouping based on common criteria
  • C. Ragged-Level Hierarchy
  • D. Customer Household
  • E. Survivorship

Answer: E

Explanation:
Master Data relationships define how different master data entities are related to each other within an organization. These relationships are crucial for understanding and managing the dataeffectively. The types of master data relationships generally include hierarchies, groupings, and associations that help in organizing and categorizing the data.
* Customer Household:
* This refers to grouping individual customers into a single household entity. It is commonly used in consumer industries to understand the relationships and dynamics within a household.
* Fixed-Level Hierarchy:
* A hierarchy with a predetermined number of levels. Each level has a specific position and relationship to other levels, such as organizational hierarchies or product categorization.
* Ragged-Level Hierarchy:
* Similar to fixed-level hierarchies, but with varying levels of depth. It accommodates entities that may not fit neatly into a fixed-level structure, providing flexibility in the hierarchy.
* Grouping based on common criteria:
* This involves creating groups or segments of data based on shared attributes or criteria. For example, grouping products by category or customers by region.
* Survivorship (NOT a relationship):
* Survivorship pertains to the process of determining the most accurate and relevant data when multiple records exist for the same entity. It is a data quality and management process, not a type of relationship.


NEW QUESTION # 73
What is a trait of a Consolidated style MDM approach?

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

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 # 74
When establishing a MOM. what is the benefit of doing data profiling?

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

Answer: B

Explanation:
* 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.


NEW QUESTION # 75
Why is a historical perspective ofMaster Data important?

  • A. Enables business analytics to determine the root cause of behavioral changes
  • B. May be required in litigation cases
  • C. Provides an audit trail
  • D. Attributes about Master Data subjects evolve over time
  • E. All of the above

Answer: E

Explanation:
* Historical Perspective of Master Data:Maintaining historical data about master data objects is crucial for various reasons.
* Reasons for Importance:
* Provides an audit trail:Keeping historical data allows organizations to track changes and understand the evolution of data over time, which is essential for auditing purposes.
* May be required in litigation cases:Historical data can serve as evidence in legal disputes, demonstrating the state of data at specific points in time.
* Attributes about Master Data subjects evolve over time:As entities change, such as customers moving or changing names, maintaining historical data allows for accurate tracking of these changes.
* Enables business analytics to determine the root cause of behavioral changes:Historical data can help in analyzing trends and identifying reasons for changes in business metrics or customer behavior.
* Conclusion:All the provided reasons collectively highlight the importance of maintaining a historical perspective of master data.
References:
* DMBOK Guide, sections on Master Data Management and Data Governance.
* CDMP Examination Study Materials.


NEW QUESTION # 76
A(n) _____ is used for detailing collaboration principles, escalation, and dispute resolution process between MDM and its data suppliers.

  • A. Warranty
  • B. Business Requirements Document
  • C. Operations Run Book
  • D. Metadata catalog
  • E. Operational Level Agreement

Answer: E

Explanation:
An Operational Level Agreement (OLA) is used for detailing collaboration principles, escalation, and dispute resolution processes between MDM and its data suppliers. Here's why:
* Purpose of an OLA:
* Collaboration Principles: Defines how MDM teams and data suppliers will collaborate, including roles, responsibilities, and communication protocols.
* Escalation Processes: Outlines the steps for escalating issues when standard resolution mechanisms are insufficient, ensuring timely and effective problem resolution.
* Dispute Resolution: Specifies methods for resolving disputes between parties, fostering a cooperative and constructive working relationship.
* Other Documents:
* Business Requirements Document: Defines business needs and requirements but doesn't typically focus on operational collaboration.
* Metadata Catalog: Describes metadata and data dictionaries, not collaboration principles.
* Warranty: Provides guarantees on products or services, irrelevant to operational collaboration.
* Operations Run Book: Details operational procedures and workflows, not specifically focused on collaboration and dispute resolution.
* References:
* Data Management Body of Knowledge (DMBOK), Chapter 8: Data Quality Management
* DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"


NEW QUESTION # 77
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