In this DBL, students get a chance to get a first glimpse on process mining. Through a practical case, students will learn the basics of data mining in the context of (business) processes and they build a prediction model for process aspects. In the basic course Data Analytics for Engineers, students have seen the basics of data analytics. In this course, we introduce a new perspective into the mix: The process perspective. Data is not just considered as a static object, but temporal aspects are considered which are causally related, i.e. the application for a loan of 20k Euro leads to a credit check being performed by a bank within 2 hours after the application. In groups, students will apply the CRISP-DM framework to first understand the data and hypothesise on the outcome of a relevant question. Then, they prepare the data and build an analysis model which is evaluated. After the evaluation, the model is either deployed, or the assumptions are revisisted in a next iteration.
- Boudewijn van Dongen - Boudewijn’s research focusses on conformance checking. Conformance checking is considered to be anything where observed behavior, needs to be related to already modeled behavior. Conformance checking is embedded in the larger contexts of Business Process Management and Process Mining. Boudewijn aims to develop techniques and tools to analyze databases and logs of large-scale information systems Read More ...