This paper provides an overall architecture to support all levels of data access and analysis against internal and external data in a variety of formats (any data, any where). This star architecture promotes interoperability between applications and databases. It promotes query optimized data warehouse. A star schema pattern language is presented to support data ware house building. The patterns are split into four main sub models: the conceptual, the logical, the physical, and the summary sub model. The model is composed of three layers: the virtual data warehouse layer (VDW), virtual data warehouse engine (VDWE), and the end user layer (EUL). The VDW layer combines all the internal and external databases as a one virtual data warehouse. The intelligent VDWE layer provides intelligent analytical processing to the decision makers. This layer also offers administrative tools for data administration. There is a dynamic metadata repository associated with the engine to support the heterogeneous joins between these different internal and external data stores. There are associated software agents to notify the engine the exception conditions occurrences. The business rules and constraints are enforced by the engine. The end user layer (EUL) encapsulates access code and allows information technology personnel to manage and optimize the model. A case study is presented to demonstrate the paper concepts.
[1]
Ralph Kimball,et al.
The Data Warehouse Lifecycle Toolkit: Expert Methods for Designing, Developing and Deploying Data Warehouses with CD Rom
,
1998
.
[2]
Yang Liu,et al.
The Prototype Research of a Web-Based DSS Intelligent Agent Over Data Warehouse
,
2004,
IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).
[3]
Timon C. Du,et al.
Designing data warehouses for supply chain management
,
2004,
Proceedings. IEEE International Conference on e-Commerce Technology, 2004. CEC 2004..
[4]
Ralph Kimball,et al.
The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
,
1996
.
[5]
Enrico Franconi,et al.
A data warehouse conceptual data model
,
2004,
Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004..
[6]
Chris Adamson,et al.
Data Warehouse Design Solutions
,
1998
.