An Analytical Study of Big Data Clustering Algorithms and its Challenges

Big Data is basically vast amount of data which cannot be effectively processed, captured, and analyzed by traditional database and search tools in reasonable amount of time. Big Data information explosion is mainly due to the vast amount of data generated by social media platform, data input from many channels, various mobile devices, user agents, multimedia data, and so on. Overall it is an expanding “Digital Universe”. Big Data predominately revolve around 5V's: Volume, Velocity, Variety, veracity, Value. Big data plays a major role in all business sectors in the digital era. The purpose of this research is to analyze the challenges of bigdata, tools and techniques used and discuss different clustering methods including Data Mining clustering algorithms, dimension reduction techniques, parallel classification and the Map Reduce framework and its challenges.