CDMP-RMD Exam Dumps : Reference And Master Data Management Exam

Ownership is a crucial principle in managing Reference and Master Data. Here’s an in-depth look at why:

Organizational Ownership:

Unified Responsibility: Reference and Master Data are assets that span across various functions and departments within an organization.

Consistency and Accuracy: Ensuring that data ownership is attributed to the organization prevents silos and ensures data is consistently accurate and available across all departments.

Data Governance: Proper governance frameworks ensure that data is managed in a way that meets the organization’s needs and complies with relevant regulations and standards.

Avoiding Departmental Silos:

Cross-functional Use: Different departments use and rely on Reference and Master Data, so ownership by a single department can lead to conflicts and inconsistencies.

Holistic Management: Centralized ownership enables holistic data management practices, enhancing data quality and usability across the 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)"

Reference data and master data serve different purposes within an organization, and storing them in separate repositories can be beneficial for managing them effectively.

Reference Data:

Reference data is used to classify or categorize other data. Examples include code tables, taxonomies, and standard lists like country codes or industry classifications.

It is often less volatile and has a higher degree of standardization.

Master Data:

Master data refers to the core business entities that are essential for operations, such as customers, products, employees, and suppliers.

It is often more dynamic and requires frequent updates to ensure accuracy and consistency across systems.

Separate Repositories:

Storing reference and master data in separate repositories allows for tailored management strategies, governance, and security measures suited to their specific needs.

This approach can improve performance, data quality, and accessibility by reducing complexity and focusing resources on maintaining each type of data appropriately.

Planned control activities are not considered master data. Here’s why:

Master Data Examples:

Categories and Lists: Master data typically includes lists and categorizations that are used repeatedly across multiple business processes and systems.

Examples: Product categories, account codes, country codes, and currency codes, which are relatively stable and broadly used.

Planned Control Activities:

Process-Specific: Planned control activities pertain to specific actions and checks within business processes, often linked to operational or transactional data.

Not Repeated Data: They are not reused or referenced as a stable entity across different systems.

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)"