Abstract
M.Com. (Information Technology Management)
The recent advancement in information technology has prompted many organisations to review their business strategies. One of the prominent areas concerning business executives is data management. The introduction of new technology such as the ‘internet of things’ continues to present serious challenges within the data management discipline. Systems that used to be siloed are now expected to share data and integrate with other systems. The integration and sharing of data across systems presents serious data management challenges. Business executives are responding to this challenge by turning to master data management.
The lack of research studies and research papers in this field show the immaturity of the master data management discipline. This makes business executives have less interest in master data management and therefore reduces any investment into research on the subject.
New data governance legislation and regulations such as those set out in the Protection of Personal Information Act are now forcing business executives to be accountable for the data they own. This presents a serious challenge for business executives as the master data management discipline has not been well-researched. The implementation of a master data management program is very challenging and the current best practices are too generic to be applicable in every company. Within the South African boundaries, there are no known master data management frameworks that can be used to facilitate the implementation of master data management programs.
This dissertation uses an exploratory, phenomenographic research approach to learn about master data management. The aim of the exploratory approach was to develop the required knowledge, establish priorities and develop the concepts of master data management more clearly. One of the challenges of implementing master data management is the identification of master data objects from the business processes.
Keywords: Enterprise information management, data management, master data management, information technology, process management, data architecture, information quality, IT portfolio management, information security.