Recently, process mining emerged as a new scientific discipline on the interface between process models and event data. Whereas conventional Business Process Management (BPM) approaches are mostly model-driven with little consideration for event data, the increasing availability of high-quality data enables management decisions based on "evidence" rather than PowerPoints or Visio diagrams. Process mining can be used to (better) configure BPM systems and check compliance. Moreover, the high-quality event logs of BPM systems allow for advanced forms of process mining such as prediction, recommendation, and trend analysis. The challenge is to turn torrents of event data ("Big Data") into valuable insights related to performance and compliance. The results can be used to identify and understand bottlenecks, inefficiencies, deviations, and risks. Process mining helps organizations to "mine their own business": they are enabled to discover, monitor and improve real processes by extracting knowledge from event logs. In his talk, prof. Wil van der Aalst will provide an overview of this exciting field that will become more and more important for BPM.
|Title of host publication||6th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2014, Rome, Italy, October 21-24, 2014)|
|Editors||A. Fred, J. Filipe, J.L.G. Dietz, D. Aveiro, K. Liu|
|Publisher||SCITEPRESS-Science and Technology Publications, Lda.|
|Publication status||Published - 2014|