A Framework to Enhance Data Quality in Master Data Management Process: A Healthcare Study

For modern enterprises to guarantee the quality and accuracy of their fundamental business data, master data management (MDM) is essential. However, a lack of connectivity between data governance and data quality throughout deployment is the reason why many MDM programs fail. This paper introduces a six-phase MDM framework that specifically integrates stakeholder-driven governance and data quality dimensions into each phase of the MDM lifecycle. Based on the PRAXEME methodology and designed using Business Process Model and Notation (BPMN), the framework emphasizes real-time monitoring and facilitates departmental collaboration. A healthcare case study illustrates its efficacy in enhancing data comprehensiveness, minimizing redundancy, and boosting operational productivity. The proposed framework offers a comprehensive approach that aligns business and IT objectives and reinforces process transparency.

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Publication Details

Journal
ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)
Published
2025-01-01
DOI
https://doi.org/10.5935/jetia.v11i55.2649
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

A Framework to Enhance Data Quality in Master Data Management Process: A Healthcare Study

Abdelhabib Bourouis, Chafika Benkherourou
ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)
Data Quality and Management
article

A Framework to Enhance Data Quality in Master Data Management Process: A Healthcare Study

Abdelhabib Bourouis, Chafika Benkherourou
article en

Abstract

For modern enterprises to guarantee the quality and accuracy of their fundamental business data, master data management (MDM) is essential. However, a lack of connectivity between data governance and data quality throughout deployment is the reason why many MDM programs fail. This paper introduces a six-phase MDM framework that specifically integrates stakeholder-driven governance and data quality dimensions into each phase of the MDM lifecycle. Based on the PRAXEME methodology and designed using Business Process Model and Notation (BPMN), the framework emphasizes real-time monitoring and facilitates departmental collaboration. A healthcare case study illustrates its efficacy in enhancing data comprehensiveness, minimizing redundancy, and boosting operational productivity. The proposed framework offers a comprehensive approach that aligns business and IT objectives and reinforces process transparency.

ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)Vol. 11(55)
University of Batna 1 (DZ), Larbi Ben M'hidi University of Oum El Bouaghi (DZ)
Openalex Percentile: Top 63%
Data Quality and Management
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