Process mining is a data analytics technique to discover, evaluate or enhance business processes by analysing the data traces left behind during the execution of these processes. It provides insights based on the data captured in the process-supporting IT systems. In contrast to other data analytic mechanisms, process mining analyses process flow, i.e. the sequence of steps taken by various actors to execute a particular task. The insights gained by process mining can be used for conformance checking or process improvement.
In this course the participants not only learn the theoretical principles underlying process mining, but they also get hands-on experience on real-life data. All relevant steps of process mining will be addressed: setting a goal, retrieving data, building an event log, applying process mining algorithms and interpreting the results. Examples are derived from various application areas, concerning internal business processes as well as customer journeys.
The course distinguishes two tracks: a theoretical track in which the theory of process mining is discussed and a practical track in which the participants execute a process mining assignment. During the entire course the participants will work in teams on a report investigating a specific process mining theme. After the course, the participants:
The balanced combination of theory and hands-on practice enables the participants to gain a comprehensive knowledge of process mining they can apply in actual environments.
Dr. ir. Marlies van Steenbergen
Students or practitioners interested in process management, automation and improvement as well as students with flair for IT or practitioners wanting to learn theory and practice on process discovery and improvement. This course can both be followed standalone and in addition to the BPM and IT course.
Provide course members with insights and practical experience in process mining.
5 days, 6-8 contact hours per day, 1-2 self-study hours per day
Housing through: Utrecht Summer School.
Marlies van Steenbergen | E: firstname.lastname@example.org