Roles and Competences of Data Science Projects

Abstract

In recent years, it has become increasingly apparent that data is playing an ever more important role in companies and the need for IT (Information Technology) applications to support people in their activities is growing. The requirements for data-driven projects for the automation and augmentation of processes and tasks are significantly higher than for standard IT projects. An essential requirement is to learn from company data and to use it for new applications. The composition of the project team plays an essential role. It is necessary to recognize which roles and competences are required for the implementation of the project and to recognize how these may change during the project. In the following, due to the interdisciplinary nature of data science projects, new competences and roles for project execution will be identified and discussed. Possible risks that can arise from unstructured project planning and from role and competence planning will be identified. The differences compared to standard projects are highlighted and the challenges compared to them are examined. To support project planning, the use of tools can be helpful. The requirements a tool or method should fulfil in order to add value for a broad spectrum of enterprises are addressed. Exemplary criteria in this context are neutrality, branch independence and free availability of the method. In addition, the usability and areas of application of such tools are discussed.

Keywords: roles, competences, data science

DOI: 10.54941/ahfe1002564