Data Science Roadmapping: Towards an Architectural Framework


KAYABAY K. , GÖKALP M. O. , GÖKALP E. , EREN P. E. , KOÇYİĞİT A.

2020 IEEE International Conference on Technology Management, Operations and Decisions, ICTMOD 2020, Marrakech, Morocco, 24 - 27 November 2020 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/ictmod49425.2020.9380617
  • City: Marrakech
  • Country: Morocco
  • Keywords: data science, big data, roadmapping, Industry 4.0, business strategy, TECHNOLOGY ROADMAP, BIG DATA, MANAGEMENT

Abstract

© 2020 IEEE.The availability of big data and related technologies enables businesses to exploit data for competitive advantage. Still, many industries face obstacles while leveraging data science to overcome business problems. This paper explores the development of a roadmapping approach to address data science challenges. Towards this goal, we customize technology roadmapping by synthesizing roadmapping, big data, data science, and data-driven organization literature. The resulting data science roadmapping approach links business strategy with data-related, technological, and organizational resources. It also enables communication, stakeholder buy-in, and project prioritization. While most of the existing studies illustrate prebuilt roadmaps, this study focuses on the process of roadmapping. The application of the roadmapping process rather than a particular roadmap provides the benefits above.