Framework to Analyze Data in Dynamic Environment for Effective Decision Making

Abstract

The man and the machine are generating voluminous and varieties of data ranging from batch data to stream data. Most of the organizations acquire any type of data from any sources and store it. The captured information is untapped in the existing systems, but it adds value only when it is used for a specific purpose. Now organizations took initiatives to recognize the value of the existing information by integrating, managing and analyzing it. The purpose of this research paper is to propose a novel framework for big data analytics to make effective decisions in an organization by aiding the various stages of the decision making mechanism. To test the correctness of proposed framework, an experiment was done with the agricultural data to predict crop yield using reengineered Artificial Neural Network (ReANN) machine learning algorithm. The result justifies the proposed framework for the decision making process, gives added value.