Leveraging Canonical Correlation Analysis for Advanced Business Analytics

Analysis is one of the important tasks performed in any business. It is important to consider before starting a new business or before making any decision related to the already existing business. In fact, every business decision revolves around the results of the analysis. Usually, business analysis is performed by humans, where the chances of mistakes are high. Also, getting accurate results regarding the estimation of factors involved in effective business analysis is a laborious process for human beings. Therefore, this paper proposes a canonical correlation methodology-based model for effective business analysis. It solves the aforesaid problems with human analysis. It considers all the critical factors of a business (example: unit price, shipping cost, expected units to be sold, etc.) and investigates how the rise and fall of these factors influence the outcome of the business (example: revenue, net income, profit, etc.). This analyzes the business ups and downs corresponding to the changes in these critical factors. These analysis results help the owners to make a decision to enhance the outcome of the business. Besides, the business planners can estimate how the relationship between different factors and their dynamic variations influences the fruitfulness of the desired business.