Business data is one of the most valuable assets, which an organization owns. Such data includes sales figures for the past few years, the loyalty of customers, and information about the impact of previous business strategies. Business data offers great potential for improving the business intelligence of an organization.
Most businesses today store huge volumes of data in data warehouses given the immense value of information contained in the data. Data mining techniques, such as neural networks are able to model the relationships that exist in data collections and consequently can be used for increasing business intelligence across a variety of business applications. The influential edited volume by Smith and Gupta presents a series of case studies from different functional areas of business to elucidate neural network technology.
As these case studies illustrate, ANNs can be used for prediction, classification, and segmentation problems across a wide variety of business areas. In recent years, ANNs have been employed in fields as diverse as engineering, statistics, marketing, finance, economics, and pharmaceuticals.