Akademik Veri Yönetim Sistemi
JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.23, ss.477-484, 2008 (SCI-Expanded)
In today's databases, large-volume data can be managed. It is impossible to figure out such a huge data without contribution of computers. In order to cope with this problem, OLAP used for summarizing, integrating, and analyzing large scale data bases. Flexible reporting and fast query can be performed by utilizing OLAP architecture. While some basic requirements could be met by existing OLAP, it is almost impossible to meet the need in case of practical huge data sets. The new OLAP architecture developed by Cetinyokus et al. (2006) makes it possible to use datacubes integratedly and also extends the ability of current OLAP tools. In this study an important phase of proposed architecture is realized. Translating to a model by using the data on data cubes developed by treated sales cube, and also recording the results got from that model to a Data Cube again, is achieved. This application is meaningful according to increasing the efficiency of OLAP tools by providing with a Decision Support.