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.