Analyzing and scripting indian election strategies using big data via Apache Hadoop framework

Abstract

When data grows beyond the capacity of currently existing database tools, it begins to be referred as Big Data. Big Data posses a grand challenge for both data analytics and database. This data is very huge in volume; it gets created at very high speed. Our work is concerned with handling huge amount of data that is concerned with different formats of elections that are been contested in India. We have created a structured database which includes thirteen different attributes providing information related to different candidates who contested MP elections from different districts of Punjab. We have opted for Apache Hadoop framework for mining and extracting relations from the database. Apache Hadoop framework makes use of Map-Reduce technology. The objective of this paper is to assist common electorates of Punjab state to take best decision on the basis of previous track record of politician or political party and decide who to vote for to get better governance.