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A review paper on big data analytics

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Author Affiliations

  • 1Computer Science and Engineering Department, Bhilai Institute of Technology, Durg, India
  • 2Computer Science and Engineering Department, Bhilai Institute of Technology, Durg, India

Res. J. Computer & IT Sci., Volume 6, Issue (1), Pages 1-5, January,20 (2018)

Abstract

In today’s world, the advancement in technology have diode to a flood of information from different domains (e.g. Scientific sensors, user-generated information, health care, web and monetary firms, and provide chain systems) over the past 20 years. The term massive information focuses on this rising trend. Additionally, to its sheer volume, massive information additionally exhibits alternative distinctive options for instance; massive information is essentially unstructured and need additional period to analyze time. This development however requires new system architectures for information possession, storage, transmission, and large-scale processing mechanisms. During this paper, we have a tendency to gift a literature survey and system tutorial for giant information analytics platforms, planning to offer Associate in Nursing overall image for non expert readers and instill a homemade spirit for advanced audiences to customize their own big-data solutions. The paper provides a broad summary of massive information analytics and discusses big information challenges. Next, we have a tendency to gift a scientific framework to dissolve massive information systems into four successive modules, particularly information generation, information acquisition, information storage, and information analytics. These four modules form an enormous information worth chain. Following that, we have a tendency to gift an in-depth analysis of diverse approaches and mechanisms from analysis and trade communities. Additionally, we have a tendency to gift the current Hadoop framework for addressing massive information challenges. Finally, we have a tendency to define many analysis benchmarks and potential analysis directions for giant information systems.

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