Metamorphosis of data (small to big) and the comparative study of techniques (HADOOP, HIVE and PIG) to handle big data

Abstract

Immoderate amount of data is being generated everyday across the world via miscellaneous sources or fields which create issues to the users. Due to this rapid growth, the crucial issue is to analyse the big data with the help of traditional data processing tactics. Structured data is not the peerless but moreover unstructured data and semi-structured data charge up the supplementary consequences to handle this voluminous data. As in this gigantic bulk of data highly advantageous information is hidden which can be good for what ails the individual, group or organization and for adding up to more sophisticated or valuable decisions. So in order to deal with this many new tools and techniques have been excogitated. These tools can analyse the large volume of data being generated at unprecedented speed. This paper shows the comparative study of some of the data analytics techniques which can untangle the big data analytics issues by examining it in more précised manner. The contrast study of Hadoop, Hive and Pig has been illustrated which covers the working of these techniques.