An Intelligent Big Data Analytics System using Enhanced Map Reduce Techniques

Abstract

An Intelligent Big Data Analytics System using Enhanced Map Reduce Techniques include a set of Methods, applications and strategy which helps the organization and industry to bring together the data and information from outside sources and internal systems, as well as it is used to collect , classify, analysis and run the queries against the data and prepare the report for effective decision making. The Enhanced Map Reduced Techniques based on K-Nearest Neighbor (KNN) clustering Strategy works efficient as well as in an effective manner. We found that the existing MR – mafia sub space clustering Strategy have not performed effectively .Many clustering techniques are adopted in real world data analysis for example customer behavior analysis, medical data analysis, digital forensics, etc. The existing MR- mafia sub space clustering Strategy is inefficient because of continuously increase in the data size, and overlaying of the data blocks .The proposed KNN clustering Strategy mainly focused on the enhanced the Map Reduce techniques, and then to avoid the unnecessary input and output data, optimize the data storage in order to achieve the best out sourcing of data privacy. The proposed KNN clustering Strategy works effectively and that can be outsourced to cloud server.