a Data & Knowledge Engineering, Department of Business Informatics, University of Linz, Altenbergerstr. 69, A-4040 Linz, Austria
b IBM India Research Lab, Block 1, I.I.T., Hauz Khas, New Delhi 110 016, India
Abstract:
Conventional data warehouses are passive. All tasks related to analysing data and making decisions must be carried out manually by analysts. Today's data warehouse and OLAP systems offer little support to automatize decision tasks that occur frequently and for which well-established decision procedures are available. Such a functionality can be provided by extending the conventional data warehouse architecture with analysis rules, which mimic the work of an analyst during decision making. Analysis rules extend the basic event/condition/action (ECA) rule structure with mechanisms to analyse data multidimensionally and to make decisions. The resulting architecture is called active data warehouse.