Abstract
Big data is termed as huge volume of both structured and unstructured dataset. When dealing with these huge dataset several challenges are encountered by the users such as analysis, capture, storage, search, transfer, sharing, and visualization. To handle these complex data sets numerous technologies have been developed such as data mining, web mining, machine learning and optimization methods. From the above technologies data mining technology is considered in this paper. Data mining technology contains various techniques such as classification, prediction and clustering etc., This paper reviews the basic concepts and clustering approaches used for big data and also a comparison study is carried out in DBSCAN, DENCLUE, and OPTICS algorithms. Each of these methods has its own pros and cons. This paper reveals that DBSCAN is efficient than the other algorithms because of its simplicity.
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