Abstract
The design of Business Intelligence (BI) systems needs the integration of different enterprise figures: on the one hand, business managers give their information requirements in terms of Key Performance Indicators (KPI). On the other hand, Information Technology (IT) experts provide the technical skill to compute KPI from transactional data. The gap between managerial and technical views of information is one of the main problems in BI systems design. In this paper we tackle the problem from the perspective of mathematical structures of KPI, and discuss the advantages that a semantic representation able to explicitly manage such structures can give in different phases of the design activity. In particular we propose a novel model of ontology for KPI, and show how this model can be exploited to support KPI elicitation and to analyze dependencies among indicators in terms of common components, thus giving the manager a structured overall picture of her requirements, and the IT personnel a valuable support for source selection and data mart design.
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Notes
- 1.
Other mathematical operators are rarer in KPI definition. They can be considered as well, without altering the generality of the following arguments.
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Diamantini, C., Potena, D. (2011). Thinking Structurally Helps Business Intelligence Design. In: D'Atri, A., Ferrara, M., George, J., Spagnoletti, P. (eds) Information Technology and Innovation Trends in Organizations. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2632-6_13
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DOI: https://doi.org/10.1007/978-3-7908-2632-6_13
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