Developing an Active Data Warehouse System

Although many data warehouse systems have been developed in recent years, the practice of data warehouse is still immature. Most of current systems have some limitations in terms of flexibility, efficiency and scalability. Furthermore, the contents of a data warehouse are becoming a large and messy jungle. It is difficult to maintain and analyze the data. Much research has been done in data mart [1; 2; 3; 4] to solve the problems. Unfortunately, the solutions isolate the information into an independent data cube. Users will only retrieve the knowledge from one single angle, but not from a global view. This is due to: ??The presented data warehouse models lack human involvement, particularly in the form of guidance and user control. ??The presented data warehouse systems do not allow users to define the relationship within data marts. To deal with the above problems, this study intends to design a novel architecture for a data warehouse augmented the active rule technique. The proposed architecture focuses on the uniform metadata model and the active monitor conditions triggered in data warehouse, which employs inference engine to go further analysis or warning.