User Profile-Driven Data Warehouse Summary for Adaptive OLAP Queries

TL;DR

This paper introduces a user profile-driven approach to adapt OLAP queries in data warehouses by creating personalized materialized views based on user preferences, enhancing decision support systems.

Contribution

It proposes a novel method for integrating user profiles into data warehouse architecture to personalize OLAP analysis through precomputed views tailored to individual preferences.

Findings

Personalized materialized views improve query response times.

User preferences effectively guide data warehouse summarization.

Implementation under SQL Server 2005 demonstrates practical feasibility.

Abstract

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