Ontology-driven Business Intelligence for Comparative Data Analysis

T. Neuböck, B. Neumayr, M. Schrefl, C. Schütz
Neub14a (2014)
Business Intelligence - Proceedings of the Third European Business Intelligence Summer School (eBISS 2013), Schloss Dagstuhl, Wadern, Germany, July 7-12, 2013, Springer Verlag, Lecture Notes in Business Information Processing (LNBIP Vol. 172), Chapter 3, ISBN 978-3-319-05460-5, pp. 77-120, 2014.
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Abstract (English)

In this tutorial, we present an ontology-driven business intelligence approach for comparative data analysis which has been developed in a joint research project, Semantic Cockpit (semCockpit), of academia, industry, and prospective users from public health insurers. In order to gain new insights into their businesses, companies perform comparative data analysis by detecting striking differences between different, yet similar, groups of data. These data groups consist of measure values which quantify real-world facts. Scores compare the measure values of different data groups. semCockpit employs techniques from knowledge-based systems, ontology engineering, and data warehousing in order to support business analysts in their analysis tasks. Concept definitions complement dimensions and facts by capturing relevant business terms which are used in the definition of measures and scores. Furthermore, domain ontologies serve as semantic dimensions, analysis graphs formally represent analysis processes, and judgement rules externalize previous insights.

Keywords: Business Intelligence, OLAP, Data Warehouses, Semantic Technologies