In this semester, the theme of the TK seminar will be Process Mining. Process Mining is a family of techniques combining data science and business process management to support the analysis of (business) processes solely based on event logs, typically recorded by enterprise information systems. These event logs contain events about what people, machines, and organizations are really doing. By using data mining, machine learning, and other related data analysis techniques, novel insights can be obtained to address performance and compliance problems of processes.
In process mining there exist mainly three categories of analysis:
- (1) process discovery, which deals with the reconstruction of a process model from an event log,
- (2) conformance checking, which checks if the reality conforms to the desired way of executing the process, and
- (3) enhancement, which enriches process models with additional information.
All three analysis categories support an analyst finding issues in a process using data-centric techniques.
The TK seminar will give a short introduction into the topic and will make you familiar with the basic terminology and techniques.
- Dozent*in: Timo Nolle
- Dozent*in: Alexander Seeliger