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Indian Journal of Public Health Research & Development
Year : 2018, Volume : 9, Issue : 2
First page : ( 436) Last page : ( 440)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2018.00163.8

Determination of Business Intelligent Using Micro Financial Analysis of Tamilnadu SME

Alexander Antony S1, Venkateswaran C. Jothi2

1Research Scholar Department of Computer Science, Presidency College, Chennai, Tamilnadu, India

2Professor, PG and Research Department of Computer Science, Presidency College, Chennai, Tamilnadu, India

Online published on 16 March, 2018.

Abstract

Financial data processing is quite obvious where per mean time the collection of data is more for business intelligent using Information and Communication Technology. Most people in urban areas financially face problems which turns their day to day life into tragedy. Business intelligence tries to budget different kinds of plans, implementing to our beloved citizens for their comfort over state government. Even though, the prediction process fails in various manners while processing large amount of dataset ends with latency and cost consumption. To overcome financial data analysis among huge data feeds, big data hadoop is required for categorized result under various sectors. In the paper proposed a YARN (Yet Another Resource Negotiator) mechanism of hadoop framework to analyze micro small and medium enterprises data of Tamilnadu financial analysis. It implements hive tool to store data in Hadoop Distributed File System (HDFS), import analysis and produce result among them. Whereas hadoop/hive uses map and reduce to compute huge datasets, tables with structured data, CSV files, etc., each cluster perform multiple mapper and reducer jobs allocated for their categorized results, and the framework effectively accumulates as well as increase in performance via parallel processing with the help of multiple map reduce method. Based on Experimental estimations, proposed YARN framework enhances the less processing time 12 minutes, high Data Size 2 GB and accuracy 22.26% of the proposed framework contrasted than previous frameworks.

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Keywords

Financial management, Hadoop Distributed File System (HDFS), data analysis, hadoop framework, hive tool, Micro small and medium enterprises (MSMEs), MapReduce, performance and Tamilnadu government.

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