Abstract
Business process redesign is increasingly motivated by analytical requirements, and data intensive activities such as image processing, prediction and classification are increasingly incorporated into business processes. Resulting business processes are referred as to data-intensive business processes. Such processes require data of various types and from different sources as well as analytical data transformations to guide and automate business process execution. Challenges associated with data-intensive business processes are identification and justification of opportunities for using advanced analytical processing methods and selection of appropriate technologies for enactment of these processes. This chapter proposes a method for specifying requirements towards data-intensive activities and uses these requirements to select appropriate implementation and enactment technologies. An example of business process redesign is discussed.
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Grabis, J. (2021). Transformation and Enactment of Data-Intensive Business Processes Using Advanced Architectural Styles. In: Zimmermann, A., Schmidt, R., Jain, L. (eds) Architecting the Digital Transformation. Intelligent Systems Reference Library, vol 188. Springer, Cham. https://doi.org/10.1007/978-3-030-49640-1_16
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