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Free PDF DAMA - Professional CDMP-RMD - Reference And Master Data Management Exam Reliable Test Practice

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DAMA Reference And Master Data Management Exam Sample Questions (Q54-Q59):

NEW QUESTION # 54
What is a Canonical Data Model?

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

Answer: A

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 # 55
All organizations have master data even if it is not labelled Master Data.

  • A. True
  • B. False

Answer: A

Explanation:
All organizations possess master data, even if it is not explicitly labeled as such. Here's why:
* Definition of Master Data:
* Core Business Entities: Master data refers to the critical entities around which business transactions are conducted, such as customers, products, suppliers, and accounts.
* Business Operations: Every organization maintains records of these entities to support business operations, decision-making, and reporting.
* Implicit Existence:
* Unlabeled Data: Organizations may not explicitly label this data as "Master Data," but it exists within various systems, databases, and spreadsheets.
* Examples: Customer lists, product catalogs, employee records, and financial accounts.
* 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 # 56
Key processing steps for successful MDM include the following steps with the exception of which processing step?

  • A. Data Model Management
  • B. Entity Resolution
  • C. Data Indexing
  • D. Data Acquisition
  • E. Data Sharing & Stewardship

Answer: C

Explanation:
Key processing steps for successful MDM typically include:
* Data Acquisition: The process of gathering and importing data from various sources.
* Data Sharing & Stewardship: Involves ensuring data is shared appropriately across the organization and that data stewards manage data quality and integrity.
* Entity Resolution: Identifying and linking data records that refer to the same entity across different data sources.
* Data Model Management: Creating and maintaining data models that define how data is structured and related within the MDM system.
* Excluded Step - Data Indexing: While indexing is a critical database performance optimization technique, it is not a primary processing step specific to MDM. MDM focuses on consolidating, managing, and ensuring the quality of master data rather than indexing, which is more about search optimization within databases.
* 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 # 57
Can Reference data be used for financial trading?

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

Answer: E

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 # 58
Master Data and metadata ran both he used to aggregate data. Master Data require* that the organization:

  • A. Include transaction audit data that describes the state of transactions
  • B. Include its transaction activity data that records details about transactions Only have one set of data as the source data and one set of data as the target data
  • C. Create a specific application solution of all the data in that application
  • D. Identify or develop a trusted version of truth for each of its entities

Answer: D

Explanation:
Master data and metadata are both used to aggregate data, but master data requires that the organization identifies or develops a trusted version of truth for each of its entities.
* Trusted Version of Truth:
* For effective master data management, an organization must establish a single, trusted version of truth for each master data entity (e.g., customer, product).
* This involves harmonizing data from various sources, resolving duplicates, and ensuring consistency and accuracy.
* Master Data:
* Master data includes critical business information that provides context for business transactions and analysis. It must be consistent, accurate, and up-to-date to support operational and analytical processes.
* Other Options:
* Transaction Activity Data:Important for operational processes but not the focus for creating master data.
* One Set of Data as Source and Target:Not sufficient for managing master data.
* Specific Application Solutions:While useful, they do not ensure the creation of a trusted version of truth for master data.
* Transaction Audit Data:Important for auditing but not central to master data creation.


NEW QUESTION # 59
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