Further information

Background

During the modeling of business processes, a large amount of data is generated that provides information on how users proceed, which steps they perform and where difficulties arise during modeling. This includes, for example, information about when a model is created, when changes are made or elements are deleted. These records offer great potential for identifying typical problems and optimization potential in process modelling. An initial implementation for recording this data has already been developed as part of the KEA-mod project. However, the rapid increase in the amount of data led to the underlying database being significantly overloaded and ultimately deactivated.

Aim of the thesis

The aim of this thesis is to investigate how the data generated during business process modeling can be stored so that the database is not overloaded. The focus is on the development and prototypical implementation of a solution within the digital modeling platform KEA-mod.