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.

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.

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 (http://bimp.cs.ut.ee/) and the Celonis Process Mining platform (https://www.celonis.com/). 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:
20% - individual assignment on quantitative analysis and simulation
20% - individual assignment on process mining
40% - group assignment on process mining
20% - exam

UPDATE-COVID19: All the assignments will comply with distance learning requirements.

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.