Abstract
The emerging area of business process intelligence aims at enhancing the analysis power of business process management systems by employing data warehousing and mining technologies. However, the differences in the underlying assumptions and objectives of the business process model and the multidimensional data model aggravate a straightforward solution for a meaningful convergence of the two concepts.
This paper presents the results of an ongoing project on providing OLAP support to business process analysis in the innovative application domain of Surgical Process Modeling. We describe the deficiencies of the conventional OLAP technology with respect to business process modeling and formulate the requirements for an adequate multidimensional presentation of process descriptions. The modeling extensions proposed at the conceptual level are verified by implementing them in a relational OLAP system, accessible via a state-of-the-art visual analysis tool. We demonstrate the benefits of the proposed analysis framework by presenting relevant analysis tasks from the domain of medical engineering and showing the type of the decision support provided by our solution.
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Mansmann, S., Neumuth, T., Scholl, M.H. (2007). OLAP Technology for Business Process Intelligence: Challenges and Solutions. In: Song, I.Y., Eder, J., Nguyen, T.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2007. Lecture Notes in Computer Science, vol 4654. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74553-2_11
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DOI: https://doi.org/10.1007/978-3-540-74553-2_11
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