Comparative Process Mining in the Cloud
In cloud computing, IT-related capabilities and resources are provided as services. This provides new opportunities for process mining. Process mining is an emerging scientific discipline can be viewed as a bridge between data science and process science: It is both data-driven and process-centric. Process mining provides a novel set of tools to discover the real processes, to detect deviations from normative processes, and to analyze bottlenecks and waste. Through cloud computing multiple organizations use the same services, but the way these services are used probably differs. This makes it appealing to learn and compare the way in which these services are really used. What are differences between processes? What kinds of effects do these differences have? Can we recommend best practices learned over event data stored in the cloud? Challenges include discovering configurable process models and process comparison. The notion of a process cube and associated operations such as slice, dice, roll-up, and drill-down are used to support process comparison. Each cell in the process cube corresponds to a set of events and can be used to discover a process model, to check conformance with respect to some process model, or to discover bottlenecks. In his keynote, Wil van der Aalst will argue that process mining can be used for learning about the actual usage of cloud services. He will introduce basic process mining concepts, explain a particular discovery technique (inductive process mining), and elaborate on his collaboration with industry. His research group at TU/e applied process mining in over 150 organizations, developed the open-source tool ProM, and influenced the 20+ commercial process mining tools available today.