Data Science Roadmapping: Towards an Architectural Framework

Date

2020-11-24

Author

KAYABAY, KEREM
Gökalp, Mert Onuralp
Gökalp, Ebru
Eren, Pekin Erhan
Koçyiğit, Altan

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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.

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85103741925&origin=inward
https://hdl.handle.net/11511/91457

DOI

https://doi.org/10.1109/ictmod49425.2020.9380617

Conference Name

2020 IEEE International Conference on Technology Management, Operations and Decisions, ICTMOD 2020

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

K. KAYABAY, M. O. Gökalp, E. Gökalp, P. E. Eren, and A. Koçyiğit, “Data Science Roadmapping: Towards an Architectural Framework,” presented at the 2020 IEEE International Conference on Technology Management, Operations and Decisions, ICTMOD 2020, Marrakech, Fas, 2020, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85103741925&origin=inward.