Big Data Analytics: An Expedition Through Rapidly Budding Data Exhaustive Era

Big Data Analytics: An Expedition Through Rapidly Budding Data Exhaustive Era

Sreenu G. (Muthoot Institute of Technology and Science, India) and M.A. Saleem Durai (VIT University, India)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/978-1-5225-2863-0.ch006
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Abstract

Advances in recent hardware technology have permitted to document transactions and other pieces of information of everyday life at an express pace. In addition of speed up and storage capacity, real-life perceptions tend to transform over time. However, there are so much prospective and highly functional values unseen in the vast volume of data. For this kind of applications conventional data mining is not suitable, so they should be tuned and changed or designed with new algorithms. Big data computing is inflowing to the category of most hopeful technologies that shows the way to new ways of thinking and decision making. This epoch of big data helps users to take benefit out of all available data to gain more precise systematic results or determine latent information, and then make best possible decisions. Depiction from a broad set of workloads, the author establishes a set of classifying measures based on the storage architecture, processing types, processing techniques and the tools and technologies used.
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Techniques And Technologies For Handling Big Data

The various techniques involved in big data scenario covers various arenas including statistics, data mining, machine learning, neural networks and optimization methods. Statistical techniques explore the correlation and causal relationship between different objectives. Data mining techniques extract valuable pattern from data through clustering, classification, regression and association rules. Big data mining techniques extend the existing algorithms to deal with huge amount of data. The main feature of machine learning is to absorb information and construct intellectual conclusions automatically.

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