Introduction: New Data Mining techniques play a very important role in the large growing biological databases. The clustering technique is an unsupervised method in data mining. Hierarchical Clustering techniques are useful to represent relationships between protein families. Objective: Bioinformatics urges the need of discovering knowledge in the vast area of molecular biology by using data mining as the core. Data Mining aims to discover hidden data from a large volume of data. Method: This paper discusses the hierarchical clustering technique of data mining on protein sequence datasets to identify genes that are consistent, easy to implement, finding and grouping the number of clusters pattern recognition. However, the valuable data is sometimes not useful but the knowledge hidden in that valuable data is meaningful. Result: The distance is used to determine how closely two organisms are related, whereas the dendrogram shows a graphical representation of the distance calculated between the clusters. Conclusion: The hierarchical clustering will help the biologist to judge which genes were clustered rightfully by viewing the tree structure. e the dendrogram. Therefore, the main aim is to unfold the knowledge in the vast field of bioinformatics by using information technologies as the key.