Bibliography | Radeschütz, Sylvia; Mitschang, Bernhard; Leymann, Frank: Matching of Process Data and Operational Data for a Deep Business Analysis. In: Proc. of the 4th International Conference on Interoperability for Enterprise Software and Applications (I-ESA 2008), Berlin, März 26-28, 2008.. University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology. pp. 171-182, english. London: Springer-Verlag, March 2008. DOI: 10.1007/978-1-84800-221-0_14. Article in Proceedings (Conference Paper).
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CR-Schema | H.2.4 (Database Management Systems)
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Abstract | Efficient adaptation to new situations of a company's business and its business processes plays an important role for achieving advantages in competition to other companies. For an optimization of processes, a profound analysis of all relevant information in the company is necessary. Analyses typically specialize either on process analysis or on data warehousing of operational data. A consolidation of business data is needed, i.e. of internal process execution data and external operational data, in order to allow for interoperability between these major business data sources to analyze and optimize processes in a much more comprehensive scope. This paper introduces a framework that offers various data descriptions to reach an efficient matching of process data and operational data, and shows its enhancement compared to separate analyses and other matching approaches.
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Full text and other links | IESA 2008
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Copyright | Springer-Verlag |
Department(s) | University of Stuttgart, Institute of Architecture of Application Systems University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
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Project(s) | BIA
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Entry date | December 19, 2007 |
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