Adapting Online Analytical Processing for Decision Modelling: The Interaction of Information and Decision Technologies

The introduction of new technologies and concepts has redefined the relative positioning of information systems (IS) and decision technologies in a corporate context. Corporate IS have been extended to include not only transaction processing databases but also analytical databases, often known as Data Warehouses. On-line analytical processing (OLAP) , as introduced by Codd et al. , is capable of capturing the structure of the real world data in the form of multidimensional tables which are known as ‘datacubes’ by management information systems (MIS) and statistical systems specialists. Manipulation and presentation of such information through multidimensional views and graphical displays provide invaluable support for the decision-maker. We illustrate the natural coupling, which exists between data modelling, symbolic modelling and ‘What if’ analysis phases of a decision support system (DSS) . In particular, we explore the power of roll-up and drill-down features of OLAP and show how these translate into aggregation and disagreggation of the underlying decision models. Our approach sets out a paradigm for analysing the data, applying DSS tools and progressing through the information value chain to create organisational knowledge.