Processing online analytics with classification and association rule mining

Business performance measurements, decision support systems (DSS) and online analytical processing (OLAP) have a common goal i.e., to assist decision-makers during the decision-making process. Integrating DSS and OLAP into existing business performance measurements hopes to improve the accuracy of analysis and provide in-depth, multi-angle view of data. This paper describes a decision support system containing our methodology, Weighted and Layered workflow evaluation (WaLwFA), extended to incorporate business intelligence using C4.5 and association rule algorithms. C4.5 produces more comprehensible decision trees by showing only important attributes. Furthermore, C4.5 can be transformed into IF-THEN rules. However, association rules are preferred as data can be described in rules of multiple granularities. Sorting rules based on rules’ complexities permits OLAP to navigate through layers of complexities to extract rules of relevant sizes and to view data from multidimensional perspectives in each layer. Experimental results on an airline domain are presented.