Synonyms and Related Terms
Definitions
Multidimensional process analytics (MPA) augments business process analytics with the multidimensional perspective on the analysis data. The latter is typically event data that is produced during the execution of process instances. Classically, business process analytics “is the family of methods and tools that can be applied to these events streams in order to support decision-making in organizations” (zur Muehlen and Shapiro 2015). On top of just looking at the event streams, MPA enables their multidimensional representation and based on this the in-depth analysis of different process perspectives, e.g., activities and resources, as well as the comparison between different process execution variants or versions.
Overview
Generally, business process analytics (BPA) is concerned with the following tasks (zur Muehlen and Shapiro 2015):
Process Controlling...
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References
Bolt A, de Leoni M, van der Aalst WMP, Gorissen P (2015) Exploiting process cubes, analytic workflows and process mining for business process reporting: a case study in education. In: Proceedings of the 5th international symposium on data-driven process discovery and analysis (SIMPDA 2015), Vienna, 9–11 Dec 2015, pp 33–47. http://ceur-ws.org/Vol-1527/paper3.pdf
Chaudhuri S, Dayal U (1997) An overview of data warehousing and OLAP technology. SIGMOD Rec 26(1):65–74. http://doi.acm.org/10.1145/248603.248616
Cordes C, Vogelgesang T, Appelrath H (2014) A generic approach for calculating and visualizing differences between process models in multidimensional process mining. In: BPM 2014 international workshops, Eindhoven, 7–8 Sept 2014, Revised papers, pp 383–394. https://doi.org/10.1007/978-3-319-15895-2_32
Grossmann W, Rinderle-Ma S (2015) Fundamentals of business intelligence. Data-centric systems and applications. Springer. https://doi.org/10.1007/978-3-662-46531-8
Kaes G, Rinderle-Ma S (2015) Mining and querying process change information based on change trees. In: Proceedings of 13th international conference, ICSOC 2015, Goa, 16–19 Nov 2015, pp 269–284. https://doi.org/10.1007/978-3-662-48616-0_17
Kriglstein S, Wallner G, Rinderle-Ma S (2013) A visualization approach for difference analysis of process models and instance traffic. In: Proceedings of 11th international conference, BPM 2013, Beijing, 26–30 Aug 2013, pp 219–226. https://doi.org/10.1007/978-3-642-40176-3_18
van der Aalst WMP (2013) Process cubes: slicing, dicing, rolling up and drilling down event data for process mining. In: First Asia pacific conference, AP-BPM 2013, Beijing, 29–30 Aug 2013. Selected papers, pp 1–22. https://doi.org/10.1007/978-3-319-02922-1_1
van der Aalst WMP (2016) Process mining – data science in action, 2nd edn. Springer. https://doi.org/10.1007/978-3-662-49851-4
van der Aalst WMP et al (2011) Process mining manifesto. In: BPM 2011 international workshops, Clermont-Ferrand, 29 Aug 2011, Revised selected papers, Part I, pp 169–194. https://doi.org/10.1007/978-3-642-28108-2_19
Vogelgesang T, Appelrath H (2015) A relational data warehouse for multidimensional process mining. In: Proceedings of the 5th international symposium on data-driven process discovery and analysis (SIMPDA 2015), Vienna, 9–11 Dec 2015, pp 64–78. http://ceur-ws.org/Vol-1527/paper5.pdf
Vogelgesang T, Kaes G, Rinderle-Ma S, Appelrath H (2016a) Multidimensional process mining: questions, requirements, and limitations. In: Proceedings of the CAiSE’16 forum, at the 28th international conference on advanced information systems engineering (CAiSE 2016), Ljubljana, 13–17 June 2016, pp 169–176. http://ceur-ws.org/Vol-1612/paper22.pdf
Vogelgesang T, Rinderle-Ma S, Appelrath H (2016b) A framework for interactive multidimensional process mining. In: Business process management workshops – BPM 2016 international workshops, Rio de Janeiro, 19 Sept 2016, Revised papers, pp 23–35. https://doi.org/10.1007/978-3-319-58457-7_2
zur Muehlen M, Shapiro R (2015) Business process analytics. In: Handbook on business process management 2, strategic alignment, governance, people and culture, 2nd edn, pp 243–263. https://doi.org/10.1007/978-3-642-45103-4_10
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Rinderle-Ma, S. (2019). Multidimensional Process Analytics. In: Sakr, S., Zomaya, A.Y. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-77525-8_97
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DOI: https://doi.org/10.1007/978-3-319-77525-8_97
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