BIG DATA FOR INDUSTRY 4.0: A CONCEPTUAL FRAMEWORK


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

International Conference on Computational Science and Computational Intelligence (CSIC), Nevada, Amerika Birleşik Devletleri, 15 - 17 Aralık 2016, ss.431-434 identifier identifier

  • Doi Numarası: 10.1109/csci.2016.87
  • Basıldığı Şehir: Nevada
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.431-434

Özet

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.