Process Mining (Wintersemester 2019/2020)
Lecturer: Prof. Dr. Henrik Leopold
(Business Process Technology)
- Weekly Hours: 2
- Credits: 3
- Enrolment Deadline: 01.10.-30.10.2019
- Teaching Form: Lecture / Exercise
- Enrolment Type: Compulsory Elective Module
- Course Language: English
Programs & Modules
- BPET-Konzepte und Methoden
- BPET-Techniken und Werkzeuge
- OSIS-Konzepte und Methoden
- OSIS-Techniken und Werkzeuge
Process mining is a family of data analysis methods that aims to discover, monitor, and improve organizational processes by analyzing data from so-called event logs. These event logs are generated by various information systems that are used in an organization and, therefore, capture how organizational processes are actually executed. The main difference to traditional data analysis techniques is that process mining explicitly focuses on the process perspective. That is, it aims to reveal the complex order relations among the activities captured in the event log. This lecture gives an introduction into the field of process mining. After introducing basic formalisms, the lecture provides a detailed and algorithmic perspective on the three key process mining technologies: process discovery conformance checking, and enhancement. What is more, it shows how process mining is currently used in industrial environments. The core idea of the lecture is to combine lectures and exercises such that students can directly apply theoretical concepts in the context of small assignments.
- Completed Bachelor's studies.
- Recommended: Process-oriented Information Systems.
- Wil van der Aalst: Process Mining: Discovery, Conformance, and Enhancement of Business Processes, Springer 2011
- Josep Carmona et al.: Conformance Checking Relating Processes and Models, Springer 2018.
- Mathias Weske: Business Process Management: Concepts, Languages, Architectures, Springer 2007
- Marlon Dumas et al.: Fundamentals of Business Process Management, Springer 2013
Lecture and Exercises.
Thursdays, 13:30-15:00; A-1.1