Chameleon is a hierarchical clustering algorithm that overcomes the limitations of the existing models and the methods present in the data warehousing. This method operates on the sparse graph having nodes that represent the data items and edges represent the weights of the data items. The representation of it allows large data set to be created and operated on successfully. The method finds the clusters that are used in the data set using the two phase algorithm. The first phase consists of the graph partitioning that allows the clustering of the data items into large number of sub-clusters. Second phases use an agglomerative hierarchical clustering algorithm to search for the clusters that are genuine and can be combined together with the sub-clusters that are produced.