Data in almost every field concerning daily needs is increasing by leaps and bounds. The problem of analysing such volume of data is enormous as tools and techniques may not be compatible of such volumes. In order to tackle the issue, data mining mechanisms are employed. Research mechanisms corresponding to big data analytics is discussed in this work. Also in case of misclassified data, it is required to tackle that data and then perform mining and classification. The mechanisms used to detect and predict anomalies along with misclassification are presented in comparative form. The objective of this work is to extract useful information regarding techniques used for big data analytics for future enhancements. Techniques used to minimise degree of misclassification in big data is analysed in comprehensive manner. These techniques extract useful patterns that could be used to observe big data in quick time.

Big data, misclassified data, data mining

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