Attributes Dimension Reduction and its accuracy in Big Data Analytics

The primary objective of this paper is to show the importance of attributes in the big data. Making business decisions from big data needs lot of time. Data mining is the process of using special algorithms/techniques to extract hidden information from large set of data. The accuracy of model result depends on the metrics. Variable selection or reduction is also one of those metrics to improve predictive power. With data is getting bigger and bigger every second, variable selection become the focus of research in recent times. Thus, objective of this paper is to explain the important algorithms and steps to select right features with high predictive power. Churn analysis will also be discussed in this paper