0841 Process Analytics
Dina Sayed Bayomie, M.S.Ph.D.
Contact details
Weekly hours
Language of instruction
09/05/22 to 11/27/22
Registration via LPIS
Notes to the course
Day Date Time Room
Thursday 12/01/22 02:30 PM - 05:30 PM Online-Einheit
Tuesday 12/06/22 02:30 PM - 05:30 PM Online-Einheit
Tuesday 12/13/22 02:30 PM - 05:30 PM Online-Einheit
Thursday 12/15/22 02:30 PM - 05:30 PM Online-Einheit
Tuesday 12/20/22 02:30 PM - 05:30 PM Online-Einheit
Thursday 12/22/22 02:30 PM - 04:30 PM Online-Einheit
Tuesday 01/10/23 02:30 PM - 05:30 PM TC.5.12
Thursday 01/12/23 02:30 PM - 05:30 PM D1.1.074
Tuesday 01/17/23 02:30 PM - 04:30 PM D1.1.074

The course covers the main concepts pertaining to the analysis of business processes from a technological perspective, from the implementation in IT systems to process mining. More in details, the arguments covers: the foundation of process implementation through Business Process Management Systems (BPMSs); the simulation of processes and their quantitative analysis; the fundamental of process mining, with a particular focus on the automated discovery of processes out of event logs and conformance checking of a process model. All the contents present an interleaving between their theoretical foundations and their practical application through analytical software.

Learning outcomes

Successful students will be able to understand and analyse the execution of business processes on IT systems. They will realize the value of data associated to processes and they will acquire the (theoretical and practical) skills to extract value out of it, e.g., they will understand the mechanisms that allow the machine-based discovery of process models out of recorded process executions. They will learn to use commercial tools used in industry for process mining.

Attendance requirements

This course is a PI type.

It is possible to be absent in one class. In case you need to miss more than one class, this must be properly justified. Please promptly contact the instructor.

Students who miss the class are required to engage in self-study to catch up with the contents.

Teaching/learning method(s)

The course is designed as a mixture of lecture with accompanying project assignments.

Both theoretical contents and hands-on sessions will be held. Tools used in the course will include the BIMP process simulator ( and the Celonis Process Mining platform ( All the tools are web services, thus accessible simply via modern web browsers.


The final grade is assigned on the basis of the following proportions:
40% - individual assignments
40% - group assignment on process mining
20% - written test

Prerequisites for participation and waiting lists

Participants are expected to be familiar with the content of the course Business Process Management. Generally, it is assumed that the concepts described in Dumas et al.: Fundamentals of Business Process Management, Springer 2013, are understood.

1 Author: Marlon Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers

Fundamentals of Business Process Management

Publisher: Springer
Edition: 2nd
Year: 2013
Content relevant for class examination: Yes
Recommendation: Essential reading for all students
Type: Book
2 Author: Wil M.P. van der Aalst

Process Mining - Data Science in Action

Publisher: Springer
Edition: 2nd
Year: 2016
Content relevant for class examination: Yes
Content relevant for diploma examination: Yes
Recommendation: Essential reading for all students
Type: Book
Recommended previous knowledge and skills

It is required that the “Process Innovation” course has been already regularly attended, and that the following notions are already acquired:

  • Business Process Management (BPM), its initiative, goals, and life-cycle;
  • business process identification, discovery, analysis, and re-design;
  • business process modelling with BPMN.
Availability of lecturer(s)
Please contact the lecturer via e-mail to fix an appointment.
Last edited: 2022-05-11