Abstract
Process models can assist in structuring and managing projects. For typical IT-projects, there are plenty process models which evolved over the last decades. Compared to them, data science process models focus on the specific challenges and aspects of data-based projects. They started evolving just before the turn of the millennium. This paper evaluates contents which could and should be included in data science process models to be useful for enterprises, especially when they are small and medium-sized or do not have their core competences in data science or IT. Regarding these contents, some existing models are analysed, providing an overview of their focus. Concluding, a vision for a continuous data science process model is given, which not only addresses the previously discussed contents, but also fulfils additional aspects to be useful in practise.
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Kutzias, D., Dukino, C., Kett, H. (2021). Towards a Continuous Process Model for Data Science Projects. In: Leitner, C., Ganz, W., Satterfield, D., Bassano, C. (eds) Advances in the Human Side of Service Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 266. Springer, Cham. https://doi.org/10.1007/978-3-030-80840-2_23
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