Tracking the effectiveness of a Reference and Master Data Management (RMDM) program requires monitoring various metrics that reflect the quality, usage, and governance of the data.The key metrics in this context are Data Quality and Data Consumption Trends, along with Access Control.
Data Quality:
Data quality metrics assess the accuracy, completeness, consistency, and reliability of the master and reference data.
Common data quality metrics include:
Accuracy:Correctness of data values.
Completeness:Presence of all required data values.
Consistency:Uniformity of data across different systems.
Timeliness:Up-to-date and current data.
Tracking data quality helps identify issues and areas for improvement, ensuring that the data remains fit for purpose.
Data Consumption Trends:
Monitoring data consumption trends involves analyzing how data is used across the organization.
This includes tracking the frequency and volume of data access, the number of users accessing the data, and the business processes that depend on the data.
Understanding consumption trends helps in identifying critical data assets, optimizing data delivery, and ensuring that the data meets the needs of its users.
Access Control:
Access control metrics track the security and governance of master and reference data.
This includes monitoring who has access to the data, how the data is accessed, and any unauthorized access attempts.
Ensuring proper access control is crucial for data security and compliance with regulatory requirements.
Value and Sustainability:
While important, these metrics focus more on the overall value and long-term viability of the RMDM program rather than specific operational effectiveness.
[Reference:, DAMA-DMBOK (Data Management Body of Knowledge) Framework, CDMP (Certified Data Management Professional) Exam Study Materials, ]
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