User Profile-Driven Data Warehouse Summary for Adaptive OLAP Queries

Data warehousing is an essential element of decision support systems. It aims at enabling the userknowledge to make better and faster daily business decisions. To improve this decision support system andto give more and more relevant information to the user, the need to integrate user's profiles into the datawarehouse process becomes crucial. In this paper, we propose to exploit users' preferences as a basis foradapting OLAP (On-Line Analytical Processing) queries to the user. For this, we present a user profiledrivendata warehouse approach that allows dening user's profile composed by his/her identifier and a setof his/her preferences. Our approach is based on a general data warehouse architecture and an adaptiveOLAP analysis system. Our main idea consists in creating a data warehouse materialized view for eachuser with respect to his/her profile. This task is performed off-line when the user defines his/her profile forthe first time. Then, when a user query is submitted to the data warehouse, the system deals with his/herdata warehouse materialized view instead of the whole data warehouse. In other words, the datawarehouse view summaries the data warehouse content for the user by taking into account his/herpreferences. Moreover, we are implementing our data warehouse personalization approach under the SQLServer 2005 DBMS (DataBase Management System).