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DAMA Reference And Master Data Management Exam Sample Questions (Q21-Q26):

NEW QUESTION # 21
Data Integration tor MDM and Reference data should:

A. Have one only one value for the same concept
B. Ignore minor changes because they will disrupt the entire system
C. Be designed to ensure timely extraction and distribution of data across the enterprise
D. Perform root analysis of data lineage at the time of integration
E. Not allow ad-hoc changes to the data

Answer: C

Explanation:
Data integration for Master Data Management (MDM) and reference data is a critical process that ensures data consistency, accuracy, and availability across the enterprise. The goal is to enable seamless data flow and access for various business functions.
* Timely Extraction and Distribution:
* Data integration processes must be designed to extract and distribute data efficiently and in a timely manner to ensure that all parts of the organization have access to up-to-date information.
* This involves implementing data pipelines and ETL (Extract, Transform, Load) processes that can handle large volumes of data and deliver it where needed without delays.
* Root Analysis of Data Lineage:
* While important for understanding data origins and transformations, root analysis of data lineage is typically part of data governance and auditing processes, not a primary focus during real-time integration.
* Ad-Hoc Changes:
* While controlled environments are important, integration processes should be flexible enough to accommodate necessary changes without compromising data integrity.
* Single Value for the Same Concept:
* Ensuring a single source of truth is essential but requires robust data governance and harmonization efforts rather than just focusing on integration.
* Ignoring Minor Changes:
* Ignoring changes can lead to data quality issues and discrepancies. Effective data integration should handle changes efficiently without causing disruptions.

NEW QUESTION # 22
Does anorganizationhave to agree to a single definition for Master Data?

A. No. financial data is master data but the definition is always changing
B. No. master data can have many definitions
C. Yes. the key thing is to agree on a standard definition
D. No. technical data may have many definitions depending on the vendor
E. No. each department can have their own definitions for master data

Answer: C

Explanation:
For effective Master Data Management, an organization must agree on a single, standard definition of master data. Here's why:
* Consistency:
* Single Definition: A standardized definition ensures consistency across different departments and systems.
* Avoids Confusion: Prevents discrepancies and misunderstandings regarding what constitutes master data.
* Data Quality and Governance:
* Unified Approach: A single definition supports unified data governance policies and data quality standards.
* Data Integration: Facilitates easier data integration and interoperability across various systems and processes.
* Business Efficiency:
* Aligned Objectives: Ensures all parts of the organization are aligned in their understanding and use of master data, leading to more efficient operations and decision-making.
* 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 # 23
Can Reference data be used for financial trading?

A. No because customer data is not considered reference data
B. No. since financial trades change every second they cannot use reference data
C. Yes. but only less than 1096 can be used
D. Yes. an estimated 70% of data being used in financial transactions is reference data
E. No. reference data is static, financial data trading is dynamic

Answer: D

Explanation:
Reference data plays a crucial role in financial trading. It includes data such as financial instrument identifiers, market data, currency codes, and regulatory classifications. Despite the dynamic nature of financial trades, reference data provides the necessary static information to execute and settle transactions. Industry estimates suggest that approximately 70% of the data used in financial transactions is reference data, underscoring its importance in the financial sector.
References:
* DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 11: Reference and Master Data Management.
* "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball and Margy Ross.
* Industry publications and whitepapers on reference data management in financial services.

NEW QUESTION # 24
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. Master data is not managed without a formal MDM program
C. Manages master data formally with a high degree of diligence and collaboration
D. A MDMprogram must include a MDM software application
E. MDM programs have a definitive life span

Answer: C

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 # 25
ISO 8000 is a Master Data international standard tor what purpose?

A. Provides a standard format for defining a model for a data dictionary
B. Define and measure data quality
C. Provide guidance only to the Buy side of the supply chain
D. To replace the ISO 9000 standard
E. Defines a format to exchange data between parties

Answer: B

Explanation:
ISO 8000 is an international standard focused on data quality and information exchange. Its primary purpose is to define and measure the quality of data, ensuring that it meets the requirements for completeness, accuracy, and consistency. The standard provides guidelines for data quality management, including requirements for data governance, data quality metrics, and procedures for improving data quality over time. ISO 8000 is not meant to replace ISO 9000, which is focused on quality management systems, but to complement it by addressing data quality specifically.
References:
* ISO 8000: Overview and Benefits of ISO 8000, International Organization for Standardization (ISO)
* DAMA-DMBOK2 Guide: Chapter 12 - Data Quality Management

NEW QUESTION # 26
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