Supervisor: Emiel Caron
The central research question of this thesis is: ‘How can (explainable) AI analytics enrich dashboards by automatically alarming for exceptional values, analyze root-causes and potentially even recommend fixes or suggest optimizations processes? ‘
The aim of this research is to enrich business dashboard with integrated explanatory analytics that are supported by mathematical models developed in Python. As a starting point, the model that is proposed by Daniels & Feelders in “A general model for automated business diagnosis” will function as our basis model. Throughout this research several subjects are tackled, for example detection of exceptional values, various techniques to prune explanations and how to extract mathematically business models from data.
At the moment Claire Vink (email@example.com) is working on this topic.