Activity and Behavior Analytics for Big Data using Parallel and Distributed Hadoop Ecosystem

Time and technology has its own role model with respect to the innovation. Technology and its model view to made things simpler for the end user; where the client need the pattern of the activity related to its domain. Information of extreme size diversity and complexity – is everywhere. This disruptive phenomenon is destined to help organizations drive innovation by gaining new and faster insight into their customers. Hence, in this paper we try to put the glimpse of the big data search mechanism in order to use the stochastic automata to see the graph or in other from which may be relevant to the client. In this aspect we have used the parallel computing the logs which already mined and transaction data in various domains in order to give a statistical data to the end user. It can be used in both the way of prevention is better than care in order to make the things smarter and better way. In this paper we have considered both the automata theory to implement the stochastic automata using Hadoop giving raise the concept of efficiency, robustness and accuracy.