The purpose of this thesis is to get a better understanding of the knowledge gap on the challenges and success factors (C&SF) that influence the success of managing data science projects (DSP) and their relationship to each other via exploratory qualitative research. This resulted in 42 unique C&SF‘s, which can be summarized in to six major categories: Value, People, Technology, Data, Process and Organization. These six major categories are used in the preparation for the interview protocol and in the Thematic Analysis procedure for the data analysis. An embedded multiple exploratory case study was done with three companies. These three cases studies were explored on several DSP’s related topics and shared many similarities and differences. Via cross case comparison all these relevant interrelated findings have led to the result of seeing a strong relationship of these findings in combination with the importance of the C&SF of having a subject matter expert (SME) actively participating in DSP’s.
Recommendations will be made on how these findings can be best used in practice and suggestions are made for future research on this topic.
- Data Science Project (DSP)
- Subject Matter Experts (SME)
- Case Studies
- challenges and success factors (C&SF)