Investigating Application and Challenges of Big Data Analytics with Clustering

Very large volumes of data analytics study the uncovering of hidden patterns, interplay, and other discoveries. Today’s technology enables data analyzing and obtaining answers practically quickly- with more conventional solutions for business intelligence, an endeavor that is longer and less effective. The demand for big data analytics has been increasing on regular basis due to the increase in engagement of users. The role of clustering is to make the big data analytic system manageable. This paper has focused on several applications that are based on clustering and big data analytics. The uses of this technology have been increasing rapidly for distance learning, health care, and IoT environment. The issues in the area of clustering and big data are also considered in this research after considering some existing researches in the relevant field. The present research has made use of an advanced mechanism to make dynamic clusters by making use of the K-mean mechanism in order to perform big-data analytics.