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A Data Quality Management System (DQMS) is a management system that deals with data quality.
The Data Quality Management System model is developed by the working group Data Quality of DAMA-NL, the Dutch chapter of Data management Association. The model is described in the white paper “A Management System for Data Quality”[1]. The elements of the DQMS are explained on the Working Group's website[2]. The model is freely available (open source).
The model shows, which elements a DQMS should contain. It is derived from the ISO 9001 standard that formulates requirements for quality management systems.
Reason for developing the model is that the terminology used in ISO 9001 is not common for data management experts. On the other hand, ISO 9001 is a well-known and commonly used standards. The model aims to bridge the gap.
As with ISO 9001, a distinction must be made between the model and the management system itself. The latter is specific to an organization and should comply with the model. It is also quite possible to use parts of the model. Management can consider getting their management system certified according to the ISO 9001 standard.
The DQMS combines well with standards such as ISO 8000 that also deal with data quality.
Objectives of a DQMS are 1) to meet data quality requirements and 2) data consumer satisfaction. These objectives are similar to the objectives of ISO 9001: meeting quality requirements and customer satisfaction.
The model divides the elements into three levels: strategic, tactical, and operational.
Strategic level
bewerken1. Leadership
2. Management Review
4. Data Quality Policy[3]
5. Data Quality Objectives
Tactical level
bewerken7. Data Suppliers
8. Communication about Data Quality
9. Roles and Responsibilities
10. Staff Competence
11. Awareness of Data Quality
12. Data Processes
13. Data Design Process
14. Continuous Improvement
15. Issue Analysis
16. Risk Analysis
17. Document Control
Operational level
bewerken18. Metadata
19. Data Quality Rules[4]
20. Critical Data Elements
21. Data Lineage
22. Data Profiling
23. Data Issues
24. Monitoring Data Quality[5]
25. Data Cleansing
References
bewerken- ↑ (en) Working Group Data Quality DAMA-NL, White paper: A Management System for Data Quality. Towards a Solid, Coherent and Standardised Approach. Working Group Data Quality of DAMA-NL.. DAMA-NL. Geraadpleegd op 3 juni 2022.
- ↑ (en) Working Group Data Quality DAMA-NL, Webpage: Working Group Data Quality DAMA-NL. DAMA-NL. Geraadpleegd op 3 juni 2022.
- ↑ (en) Working Group Data Quality DAMA-NL, Factsheet: Data Quality Policy. DAMA-NL. Geraadpleegd op 3 juni 2022.
- ↑ (en) Working Group Data Quality DAMA-NL, Factsheet: Data Quality Rules. DAMA-NL. Geraadpleegd op 2022-06003.
- ↑ (en) Working Group Data Quality DAMA-NL, Factsheet Data Quality Monitoring. DAMA-NL. Geraadpleegd op 3 juni 2022.