Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/3516
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dc.contributor.authorFakier, Muhammad Naasihen_US
dc.contributor.authorDe la Harpe, Arethaen_US
dc.date.accessioned2016-02-12T07:55:31Z-
dc.date.available2016-02-12T07:55:31Z-
dc.date.issued2008-
dc.identifier.citationFakier, M.N. & De la Harpe, R. (2008). Best data administration practices for data migration: a literature study in the healthcare industry. In A.O. Bada & P. Musa (eds). Proceedings of IFIP WG 9.4-University of Pretoria Joint Workshop, Pretoria, South Afrika, pp 17-35en_US
dc.identifier.urihttp://hdl.handle.net/11189/3516-
dc.description.abstractThis paper investigates the most practical and effective data administration concepts in order to improve data migrations, especially in healthcare systems. Currently healthcare is experiencing an increase in heterogeneous environments due to new mergers and acquisitions. One of the main concerns is identifying similar data between different systems during migrations. This leads to project scopes being exceeded because of a lack of effective data administration practices. The aim of this article is to explore best practices for migrating data and to structure this into a basic framework so that it can be adapted to almost any IT environment. Best practices identified include data modelling, data cleansing and information repository. The framework is further applied to a medical aid administrator case to demonstrate its ease of use. The results from the case prove that our framework is both simple and effective in its application, optimising on time and effort for current and future projects.en_US
dc.language.isoenen_US
dc.publisherInternational Federation for Information Processing and University of Pretoriaen_US
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/3.0/za-
dc.subjectData administrationen_US
dc.subjectMigrationen_US
dc.subjectData modelen_US
dc.subjectData cleansingen_US
dc.subjectRepositoryen_US
dc.titleBest data administration practices for data migration: a literature study in the healthcare industryen_US
dc.type.patentOtheren_US
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