Incorporation of succesful Agile elements in Data Science Development processes
: How a possible model is perceived by experts

  • M.C. (Mariska) Blasweiler

    Student thesis: Master's Thesis


    This research gives answer to the research question How to incorporate the Agile methodology into Data Science projects to gain flexibility? To get this answer a theoretical framework is built based on known Data Science development processes and Agile methods. The aim of the framework is to research which development process and Agile methods best fit together. This is a combination of CRISP-DM as the development process, KANBAN and SCRUM. The latter two are Agile methods.
    From this a SCRUMBAN model was created. This model was reviewed by consultants through a demonstration and interview. The results were then sorted and evaluated on four criteria: feasibility, completeness, usability and effectiveness. It was concluded that the model met all four criteria although effectiveness is only a perceived effectiveness. With little changes to the model, it is ready to use in practice to test if the model is effective.
    Date of Award19 Aug 2019
    Original languageEnglish
    SupervisorRemko Helms (Examiner) & Jeroen Baijens (Co-assessor)


    • SCRUM
    • KANBAN
    • Data Science process
    • Knowledge Discovery
    • Agile

    Master's Degree

    • Master Business Process management & IT (BPMIT)

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