CDMP CDMP-RMD Syllabus Exam Questions Answers

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.

Taxonomic reference data involves categorizing and organizing data to enable structured access and retrieval. It facilitates content classification, allowing for efficient multi-level navigation, which is essential for Business Intelligence (BI) activities. By organizing data into a taxonomy, users can easily locate and analyze information, supporting better decision-making processes in BI.

References:

DMBOK (Data Management Body of Knowledge), 2nd Edition, Chapter 11: Reference & Master Data Management.

DAMA-DMBOK Functional Framework, Function: Reference & Master Data Management.

Master data metadata provides crucial information about the master data, offering context and supporting its management and use within the organization.

Who, What, and Where Context:

Metadata provides descriptive information about the master data, including details about who created or modified the data, what the data represents, and where it is used.

This contextual information is essential for understanding the origins, purpose, and usage of the master data.

Includes a Sample of Content:

While metadata might include examples or samples of the data, this is not its primary purpose.

Improving Fit-for-Purpose Choices:

Metadata helps improve the application and governance of master data by providing context and supporting data management decisions.

Securing the Content:

Metadata itself is not primarily focused on security, though it can support data governance and access control processes.

Technical or Business Perspectives:

Metadata can encompass both technical and business perspectives, providing a holistic view of the data's context and usage.

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.