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Master data identification in public sector organisations

Haneem, F. and Kama, N. and Azmi, A. (2016) Master data identification in public sector organisations. Advanced Science Letters, 22 (10). pp. 2999-3003. ISSN 1936-6612

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Abstract

The Master Data Management (MDM) establishment in public sector improves the government administration efficiency by encouraging the resource sharing, data collaboration and citizen-centeredness. Nevertheless, defining master data in public sector organisations during initial activity in establishing the MDM is a very challenging process. Organisations had difficulties in identifying the master data in their organisations due to the unclear definition of master data in the public sector. Furthermore, less attention is given in the existing literatures in the MDM area for public sector. Hence, this study aims to identify and categorise the master data in public sector organisations by using a qualitative approach. It involves participative case studies from nine Malaysia’s public sector organisations and experts’ opinion to determine and categorise the master data in Malaysia’s public sector organisations. The result of this study determines master data in the public sector as core information of the organisation, shareable between business units and focusing on the service delivery to the citizens and generally grouped into three main categories; service providers, services and customers’ profile. This study presents a significant contribution to the MDM research area by providing better explanations for master data identification in public sector organisations. With regards to the practical implication, this paper can serve as reference in establishing MDM initiatives in the public sector.

Item Type:Article
Uncontrolled Keywords:Master data management (MDM), Public sector organisations
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Advanced Informatics School
ID Code:71984
Deposited By: Fazli Masari
Deposited On:23 Nov 2017 01:37
Last Modified:23 Nov 2017 01:37

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