A new OLAP architecture for integrated using of data cubes

In today's databases, management of the data by terabytes is usual. Online Analytical Processing (OLAP) is used for summarizing, integration and analyzing in large volume and detailed databases that can not be envisaged easily by human. Data Cubes (DCs) can be used both to accelerate the processes on OLAP and to make the used model more understandable. Since Cubes define a specific area, they can give faster and effective response in the queries. Simple requirements which are impossible to be met on large volume of data sets in practice can easily be done by available OLAP tools. Usage of Data Cubes for this aim will provide developments of more advantageous systems in various areas. In this study, OLAP based a new architecture is proposed for the purpose of providing decision support at higher level, thereby integrating DCs. For the sake of this architecture, by using OLAP advantages, it is possible to obtain structure in which DCs are related with each other, external data and varied analytic algorithms.