Clustering is the most frequently used physical architecture in data fusion, causing a problem as it has random distribution within local clusters, we propose a density peak based clustering algorithm utilizing a hierarchical approach. As a proficient method to joint decision-making of multi sensors, data fusion contains several benefits in data mining. In this work, we use the Salp Swarm Optimizer (SSO) algorithm based Hierarchical Density Peak Clustering (DPC) method to cluster the multiple sensor nodes as per the data similitude for the process of data fusion. Here, the higher density, distance and the cut off values are determined by using the SSO algorithm and then the chosen optimal fixed values were used to further process. Hierarchical Density Peak Clustering estimates the density and distance of each point. It is validated experimentally and compared it with the datasets and the error prediction with the test case numbers. The experimental results of the method are 96% accuracy determined from different datasets.

Many Business worth billions and trillions of dollars have gone waste in the past due to lack of proper security techniques used for Analyzing frequently used data sets resulting into potential thread to the firms and customers privacy data. The organizations are in dire need of getting the frequently used data analytics so that they can get the insight of the data and better security plan and get maximum benefit from that. Organizations are providing enormous software solutions to solve real world problems. In order to keep the business alive and excellence in the upcoming era, a deep understanding of change in underlying technology trends (cloud, big data and etc.,), Analytics and change in business dynamics. Frequently used data is the key to the success of new and existing Business strategy. The ability to capturing the frequently used data quickly for system critical application using right data analytics and protecting them with proper security will save organizations fame, time and money. In this case study will discuss about DFDM. Data Analytics Frequently used Data Management (DFDM) is a solution that helps to capture the accurate frequently used data and protect the data for any applications.