A Knowledge-driven Data Warehouse Model for Analysis Evolution

被引:0
作者
Favre, Cecile [1 ]
Bentayeb, Fadila [1 ]
Boussaid, Omar [1 ]
机构
[1] Univ Lyon 2, ERIC Lab, 5 Av Pierre Mendes France, F-69676 Bron, France
来源
LEADING THE WEB IN CONCURRENT ENGINEERING: NEXT GENERATION CONCURRENT ENGINEERING | 2006年 / 143卷
关键词
Data Warehouse; Schema Evolution; Knowledge; Rule;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A data warehouse is built by collecting data from external sources. Several changes on contents and structures can usually happen on these sources. Therefore, these changes have to be reflected in the data warehouse using schema updating or versioning. However a data warehouse has also to evolve according to new users' analysis needs. In this case, the evolution is rather driven by knowledge than by data. In this paper. we propose it Rule-based Data Warehouse (R-DW) model, in which rules enable the integration of users' knowledge in the data warehouse. The R-DW model is composed of two parts: one fixed part that contains a fact table related to its first level dimensions, and it second evolving part, defined by means of rules. These rules are used to dynamically create dimension hierarchies, allowing the analysis contexts evolution, according to an automatic and concurrent way. Our proposal provides flexibility to data warehouse's evolution by increasing users' interaction with the decision support system.
引用
收藏
页码:271 / +
页数:2
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