2019International Journal of Innovative Technology and Exploring EngineeringOpen access

Big Data Analytics for Deriving Business Intelligence Rules

Chandrashekar D K, K. R. Venugopal, K. C. Srikantaiah

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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.

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What this paper is about

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.

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Available 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.

Key concepts: Big data, NoSQL, Business intelligence, Data science, Computer science, Analytics, Scalability, Business analytics

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