In this paper we describe the concepts of automatic analysis for the exceptional patterns which are hidden in a large set of business data. These exceptions are interesting to be investigated further for their causes and explanations, as they provide important decision support. The analysis process is driven by diagnostic drill-down operations following the equations of the information structure in which the data are organised. Using business intelligence, the analysis method can generate explanations supported by the data. The methodology was tested on a case study and was reflected in considering the practical aspects of its application procedure.
|Title of host publication||Proceedings of the 26th Bled eConference|
|Editors||Dianne Lux Wigand, et al|
|Place of Publication||Bled|
|Publication status||Published - 2013|
Liu, L., & Daniëls, H. A. M. (2013). Analysis for detecting and explaining exceptions in business data. In D. Lux Wigand, & et al (Eds.), Proceedings of the 26th Bled eConference (pp. 349-358). Unknown Publisher.