For the analysis of business, a lot of research attention in the field of computational statistics and data mining has been made. Due to recent technological advances in the field of data clustering, the researchers face ever-increasing challenges in extracting relevant information from enormous volumes of available data. The paper focus on large data sets obtained from online web visiting and categorizing this into clusters according some similarity it helpful tool for the top level management to take optimized and beneficial decisions of business expansion. Clustering is the assignment of a set of observations into subsets. Cluster analysis is widely used in market research when working with multivariate data from surveys. Market researcher partition the general population of consumers into market segments and understand the relationships between customers. To achieve robustness and efficiency in data clustering combine Partitional and hierarchical (Optimized K-means algorithms) satisfiable clustering results.

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Clusters Partitional Algorithm K-means Optimized K-means Hierarchical Algorithm Single Link Algorithm