Data currency quality satisfaction in the design of a data warehouse

A Data Warehouse (DW) is a large collection of data integrated from multipl e distributed autonomous databases and other information sources. A DW can be seen as a set of materialized views defined over the remote source data. Until now research work on DW design is restricted to quantitatively selec ting view sets for materialization. However, quality issues in the DW desig n are neglected. In this paper we suggest a novel statement of the DW desig n problem that takes into account quality factors. We design a DW system ar chitecture that supports performance and data consistency quality goals. In this framework we present a high level approach that allows to check wheth er a view selection guaranteeing a data completeness quality goal also sati sfies a data currency quality goal. This approach is based on an AND/OR dag representation for multiple queries and views. It also allows determining the minimal change propagation frequencies that satisfy the data currency q uality goal along with the optimal query evaluation and change propagation plans. Our results can be directly used for a quality driven design of a DW .