A business intelligence framework for business performance using data mining techniques

Business Intelligence is a key means to promote core competence of enterprise. This paper discusses the business intelligence framework for business performance using data mining techniques. Business performance can be measured by applying bankruptcy prediction. This Business Intelligence framework consists of Quantitative bankruptcy prediction components, Qualitative Bankruptcy prediction components and a Customized reporting. In the quantitative bankruptcy prediction we are finding important financial features using Real Genetic Algorithm and applying those features in Case Based Reasoning to retrieve and predict the business performance quantitatively. In qualitative bankruptcy we are finding the qualitative bankruptcy features using Expert analysis. These qualitative features are applied in Ant Miner Algorithm to predict business performance qualitatively. Customized business intelligence reporting is delivering right information to the right user in the way they want them to be presented. We are using a Fuzzy Multi Criteria Decision Support System (FMCDS) for customized reporting. Experimental result shows more than 90% accuracy level between reference value and experimental value in quantitative feature selection.