Big Data Analytics for Deriving Business Intelligence Rules
Chandrashekar D K1, Srikantaiah K C2, Venugopal K R3

1Chandrashekar D K*, Assistant Professor in the Department of Computer Science and Engineering at S J B Institute of Technology, Bangalore, India.
2Srikantaiah K C, Professor in the Department of Computer Science and Engineering at S J B Institute of Technology, Bangalore, India.
3Venugopal K R, Vice-Chancellor of Bangalore, University

Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 1629-1633 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4636119119/2019©BEIESP | DOI: 10.35940/ijitee.A4636.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Big data is a large volume of data pool and processing and analyzing these data is tedious jobs. The aim of fulfilling huge information storage needs is that the structural transformation of repository system using traditional approaches to NoSQL technology. However, the existing technologies for storage are inefficient since, they do not generated data that are scalable, consistent and solutions for rapidly evolving diversified data. The primary method for storing huge amounts of data is used for analytics in real time applications like healthcare, scientific experiments, e-business and networks. In this paper, it is in sighted the characteristics, application, tools of big data, Technologies, Big data analytics, challenges and issues in Big data.
Keywords: Big Data Analytics, Hadoop, Map Reduce Structured Data, Semi Structured and Unstructured Data
Scope of the Article: Big Data Analytics