An Association Rule Mining for Materialized View Selection and View Maintanance

Data warehouse (DW) is a repository with query interface in support of Decision support systems. DW required answering many complex queries, managerial level queries and analytical queries, needing to develop advanced computing techniques. The DW system process involving data modeling, ETL process, query interface and reporting system. Materialized views (MV) are the pre calculated views which are used to increase the DW system performance. MV selection and maintenance need to adopt new trends and techniques. Data mining (DM) is the process of extracting hidden useful information from huge data bases . Literature of Data Mining (DM) involving algorithms and techniques related to association, classification and clustering. Recent researches shown Data mining can also be used in optimization of calculating MV's. In addition to DM techniques are also used in efficient calculation of Data cubes. This paper proposed frequent rule mining on of the Data mining approach for the selection and maintenance of MV'S. By using the advanced concepts of frequent mining algorithm the query response time can be decreased. The approach also combines the advanced techniques to accommodate the changes in updating the base data so as to increase the performance of existing MV'S selection and maintenance approaches.