BIG DATA FOR INDUSTRY 4.0: A CONCEPTUAL FRAMEWORK

Date

2016-12-17

Author

Gökalp, Mert Onuralp
Kayabay, Kerem
Eren, Pekin Erhan
Koçyiğit, Altan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While there is an abundance of tools available in the market, they are underutilized by organizations due to their complexities. Deployment and usage of big data analysis tools require technical expertise which most of the organizations don't yet possess. Recently, the trend in the IT industry is towards developing prebuilt libraries and dataflow based programming models to abstract users from low-level complexities of these tools. After briefly analyzing trends in the literature and industry, this paper presents a conceptual framework which offers a higher level of abstraction to increase adoption of big data techniques as part of Industry 4.0 vision in future enterprises.

Subject Keywords

Industry 4.0, Big data, Data flow based programming languages, Machine learning, Data mining

URI

https://hdl.handle.net/11511/29991

DOI

https://doi.org/10.1109/csci.2016.87

Collections

Graduate School of Informatics, Conference / Seminar

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Citation Formats

M. O. Gökalp, K. Kayabay, P. E. Eren, and A. Koçyiğit, “BIG DATA FOR INDUSTRY 4.0: A CONCEPTUAL FRAMEWORK,” 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/29991.