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Sustainable Business Intelligence Systems : Modelling For The Future / Roelien Goede

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Business intelligence systems are used in support of strategic decision-making in organisations. Strategic decisions in support of the sustainable development goals require accurate and accessible data. Of equal importance is the sustainability of the business information systems themselves. Not only should they be sensitive to resource consumption but they should also be designed for the future needs of the organisation. We argue that sustainable business intelligence systems should represent as many perspectives in the organisation as possible supported by the available data. In order to achieve this, a critical (Kantian) systems perspective is suggested that foster appreciation of different perspectives in the organisation. Prevailing belief in the business intelligence system industry is that a key business problem should drive development of the system. Our position is more future oriented in that we argue that inclusion of all available perspectives on business problems will prolong the life of the system, thereby making it more sustainable. This is not an idealistic requirement when a data vault is used for the data model of the system. Contrary to the more common dimensional modelling, data vault modelling does not require restrictive decisions to be made on the scope of the system. In fact, the worst-case scenario is addressed in the initial model. The paper provides a conceptual discussion of how a business intelligence system should be designed and developed to ensure that it is sustainable. Since the right system should be developed in the right way, we incorporate known success factors into our discussion. We argue that the critical (Kantian) systems perspective can lead to the right system and that data vault modelling in context of lessons from identified success factors is the right way to develop the business intelligence system.

Level
Postgraduate
Subject
Education
Type
Inaugural Lecture
Institution
North-West University
Language
English
Year
2019
Pages
11 pages
File size
2.74 MB
Format
PDF
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