Business Process Intelligence (BPI) is an emerging topic that has gained popularity in the last decade. It is driven by the need for analysis techniques that allow businesses to understand and improve their processes. One of the most common applications of BPI is reporting, which consists on the struc-tured generation of information (i.e., reports) from raw data. In this article, state-of-the-art process mining techniques are used to periodically produce automated reports that relate the actual performance of students of Eindhoven University of Technology to their studying behavior. To avoid the tedious manual repetition of the same process mining procedure for each course, we have designed a work-flow calling various process mining techniques using RapidProM. To ensure that the actual students' behavior is related to their actual performance (i.e., grades for courses), our analytic workflows approach leverages on process cubes, which enable the dataset to be sliced and diced based on courses and grades. The article discusses how the approach has been operationalized and what is the structure and concrete results of the reports that have been automatically generated. The reports were sent to lecturers and feedback was collected through an evaluation form. Also, we analyzed an example report to show the range of insights that they provide.
|Name||CEUR Workshop Proceedings|
|Conference||5th International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2015|
|Period||9/12/15 → 11/12/15|
- Analytic Workflows
- Busineb Proceb Reporting
- Proceb Cubes
- Proceb Mining