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

Registry style MDM involves maintaining a central registry that stores references to master data while allowing the actual data to remain in the source systems. This approach requires technologies that support data integration and real-time access without physically moving the data.

JSON Mapping:

JSON mapping is useful for data exchange but does not specifically support the registry style MDM approach.

ETL Toolset:

ETL (Extract, Transform, Load) tools are typically used for batch data processing and integration, which may not align with the real-time data access requirements of a registry style MDM.

Columnar Database:

Columnar databases are optimized for analytical queries but are not specifically designed for supporting registry style MDM.

Complex Queries:

While complex queries can be part of the data access strategy, they are not a comprehensive solution for registry style MDM.

Data Virtualization:

Data virtualization provides a unified view of data from multiple sources without physically moving the data. It supports real-time data access and integration, making it well-suited for registry style MDM.

It enables organizations to access and manage master data across different systems while maintaining a central registry for reference.

The ISO definition of Master Data quality focuses on the degree to which the data's characteristics meet the requirements of individual users. This implies that quality is subjective and depends on whether the data is suitable and adequate for its intended purpose, fulfilling the specific needs of its users.

References:

ISO 8000-8:2015 - Data quality — Part 8: Information and data quality: Concepts and measuring.

DAMA-DMBOK: Data Management Body of Knowledge (2nd Edition), Chapter 13: Data Quality Management.

The Reference Data Change Request Process typically involves the following sub-processes:

Receive Change Request:

Initiation: The process begins with the receipt of a change request, formally logged and acknowledged.

Identify Stakeholder:

Stakeholder Identification: Identifying all relevant stakeholders who need to be involved or informed about the change.

Identify Impact:

Impact Analysis: Assessing the potential impact of the requested change on existing systems, processes, and data.

Decide and Communicate:

Decision Making: Reviewing the change request, making a decision, and communicating the outcome to stakeholders.

Excluded Step - Monitor Database Change: While monitoring database changes is important for overall data management, it is not typically part of the specific change request process for reference data. This step pertains more to ongoing operational monitoring rather than the change request workflow.

References:

Data Management Body of Knowledge (DMBOK), Chapter 6: Data Development & Maintenance

DAMA International, "The DAMA Guide to the Data Management Body of Knowledge (DMBOK)"