Score Higher on Verified CDMP-RMD | Reference And Master Data Management Exam Questions with Answers

Master Data Management (MDM) involves various processes and technologies to ensure that master data is accurate, consistent, and trustworthy. The most comprehensive definition of MDM captures its multi-faceted nature, encompassing governance, technology, and organizational roles.

Governed Processes:

MDM involves establishing governance processes to define policies, standards, and procedures for managing master data.

These processes ensure that data is handled consistently and according to defined rules.

Role of People and Technologies:

Effective MDM requires the involvement of people, including data stewards, data owners, and governance committees, who are responsible for overseeing and managing master data.

Technologies, such as MDM software and tools, facilitate the implementation of governance processes, data integration, data quality management, and synchronization.

Key Objectives:

Master data should be understood by stakeholders, ensuring clarity and common understanding of data definitions and attributes.

Trust in master data is achieved through rigorous data quality and governance practices.

Data should be controlled, meaning that access, usage, and changes to the data are managed and monitored.

Master data must be fit-for-purpose, meeting the specific needs and requirements of the organization’s business processes.

The format and allowable ranges of Master Data values are primarily dictated by business rules.

Business Rules:

Business rules define the constraints, formats, and permissible values for master data based on the organization’s operational and regulatory requirements.

These rules ensure that data conforms to the standards and requirements necessary for effective business operations.

Semantic Rules:

These rules pertain to the meaning and context of the data but do not directly dictate formats and ranges.

Processing Rules:

These rules focus on how data is processed but not on the allowable values or formats.

Engagement Rules:

These rules govern interactions and workflows rather than data formats and ranges.

Database Limitations:

While database limitations can impose constraints, they are typically secondary to the business rules that drive data requirements.

Managing master data elements can be performed at multiple levels within an organization. This includes third-party providers such as Dun & Bradstreet (D&B) which can supply enriched and standardized master data. At the enterprise level, organizations manage master data centrally to ensure consistency and quality across all systems and processes. Within application suites suchas ERP (Enterprise Resource Planning) systems, master data management ensures that data is consistent and accurate within and across different applications. Therefore, master data elements can be managed at all these points.

References:

DAMA-DMBOK2 Guide: Chapter 10 – Master and Reference Data Management

"The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball