BUSINESS INTELLIGENCE APPRAISAL OF AUGMENTED DATA BASED ON EXISTING CUSTOMERS’ DATASET OBTAINED BY GENETIC ALGORITHM USING MULTIPLE CORRELATION TECHNIQUE

Abstract: The major issues in the business intelligence is to predict the customer behavior and understanding them for the betterment of the business. This understanding and behavior are to be analyzed on the basis of the information given by the customer. It is important to determine customer preferences in formulating market strategies that is taken from the concept of Business Intelligence (BI) and analysis. This analysis is based on the customer profile. For these kinds of analysis, a large number of datasets are required. Having analyzed the data set in the paper [1], it was realized that more number of dataset will give maximum precession. To get these kinds of data set formulated for the work, is very difficult. This is the reason, the work has been concluded to go for genetic algorithm to generate new groups of datasets to augment the existing one, with a proper validation. Also, it has been decided to give more priority for the correlation by effectively using multiple correlation, to get an appropriate result in this work.

Keywords: Business Intelligence (BI), Multiple Correlation Technique, Augmented Data, Genetic Algorithm.