Clustering is important part in Data mining. Clustering is a technique, in which data is using in the form of clusters. A set of objects divided into groups these groups called clusters. K-MEANS is a basic type of clustering technique. It is an unsupervised learning. K-means clustering is a simple technique, which is use to group items into k clusters. BIRCH is one of the famous methods, which used with the k-means to improve the quality of data, which are present in clusters. BIRCH is an (Balanced Iterative Reducing and Clustering using Hierarchies). Birch is a scalable clustering method, which mainly designed for very large data sets. In this paper we discussed about review of other clustering technique which are used by others researchers for data mining. We also discussed the limitations and applications of clustering techniques, which are most popular for data mining. This paper also represents a current review about the K-MEANS and BIRCH algorithm.

Data Mining, Clustring, K-Means Clustering, Birch Clustering

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