Applying clustering algorithm to analyze the data from different dimensions

Abstract

In today's data-driven panorama, the ability to analyze information to drive decision-making and resolve problems is fundamental for success. This requires a robust, effective, flexible, data analytics that assists to build accurate predictive versions quickly and intuitively. Data analysis is a common technique used to analyze data in various fields of modern scientific research, which includes different divisions of Data analytics include many techniques. Clustering is considered as one of the unsupervised learning technique for analyzing the data. With the increase in number of disciplines, the amount of data is also increased. This results in the development of various tools and algorithms for applying cluster analysis. Each of the clustering algorithm has its own advantages and limitations and it completely depends on the complexity of available information. The current research is an attempt to analyze the data using clustering techniques. The researcher use python language to compile a program to collect the data from an enterprise's information management system. Python is used to analyze and clusters are interpreted accordingly. The results of clustering data based on different dimensions will lead to improve knowledge about the data accordingly.