Novel Approaches for Data Summarization of Large and Multidimensional Datasets

Abstract

These days in the data warehouse domain data mining and visualization techniques play a major role in almost all the core business processes of any organization Various methods are already available in the market to extract data from various heterogeneous sources and store it into homogeneous sources called data warehouses Using data warehouses various data analysis techniques such as classifiers clusters association rule mining sequential pattern mining linear regression and so on are applied to extract the hidden patterns in the voluminous data These extracted patterns play an important role in the organization for decision making in various business process To understand the various patterns derived from a data warehouse using data analysis we need to represent them in suitable visualization techniques to understand them in a better way newline