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Literature survey on Big Data Analytics

Mallikarjuna Reddy Beram, , , ,

Affiliations
Lead I, UST Global, Bengaluru, Karnataka 560066, India,

:10.22362/ijcert/2018/v5/i8/v5i801

Abstract

In this latest era of computer’s, a enormous amount of data is available to managerial. Big data doesn’t only refer to datasets that are big, but also high in volume, velocity, value, veracity and variety, which is tough to handle using old-fashioned tools and methods. Due to rapid growth of such data, some ways are necessary to found to get important knowledge and values from these data sets. Also, decision makers need to gain some valuable vision from such big and endlessly changing data, ranging from daily transactions to customer connections and data of social network. Such vision can be given using Big Data Analytics, which is the application of Advanced Analytics Technique on big data. This paper aims to literature of some of the analytics methods and tools which can be applied to big data, as well as the charge provided by the applications of big data analytics in different decision domain. We have discussed the different processing techniques for big data and processing steps as well.

Citation

Mallikarjuna Reddy Beram."Literature survey on Big Data Analytics". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.5, Issue 8,pp.1-5, August - 2018,

Keywords : Big Data Analytics, Advanced Analytics, Transactions Data, Data processing.

References

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[14]. Zaharia, M. Chowdhury, T. Das, A. Dave, J. Ma, M. McCauley, M. Franklin, S. Shenker, and I. Stoica. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. Technical Report UCB/EECS-2011-82, EECS Department, University of California, Berkeley, 2011
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DOI Link : https://doi.org/10.22362/ijcert/2018/v5/i8/v5i801

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Citation Index

Citations Indices	All
Citations	1026
h-index	14
i10-index	20
Source: Google Scholar

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Acceptance Rate (By Year)
Year	Rate
2021	10.8%
2020	13.6%
2019	15.9%
2018	14.5%
2017	16.6%
2016	15.8%
2015	18.2%
2014	20.6%

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