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Performance Comparison of Statistical Techniques with Big Data Analysis

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Stuti Mehla, Saurabh Upadhyay
10.5120/ijca2017914770

Stuti Mehla and Saurabh Upadhyay. Performance Comparison of Statistical Techniques with Big Data Analysis. International Journal of Computer Applications 169(6):25-28, July 2017. BibTeX

@article{10.5120/ijca2017914770,
	author = {Stuti Mehla and Saurabh Upadhyay},
	title = {Performance Comparison of Statistical Techniques with Big Data Analysis},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2017},
	volume = {169},
	number = {6},
	month = {Jul},
	year = {2017},
	issn = {0975-8887},
	pages = {25-28},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume169/number6/27990-2017914770},
	doi = {10.5120/ijca2017914770},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In present scenario computers are involved in every field of daily life, leads to increment in volume ,variety and velocity of data. It makes difficult for Conventional Statistical techniques to handle these huge datasets and results in emergence of Big Data and different tools such as Hadoop, Hive for analyzing it. This paper describes the generic statistical techniques such as classification, regression and tools for analyzing Big Data. Analytical Comparison of these tools on different aspects are also explained.

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Keywords

Big Data, IOT, Hadoop, HDFS, MapReduce analytics, Hive.