Intelligent Data Compression Approach in Multidimensional Data Warehouse

The problem with MOLAP is that large tables should be loaded in main memory, which can slow the system, even saturate the memory. In this work, we present a new compression method, called BTC, for multidimensional data warehouses. Several methods have been proposed in the literature that can compress the data such as the Bitmap method. The main purpose of BTC is to improve the access time on data. This technique is based on the concept of B-Tree. We implemented this new method, and then we compared and analyzed it with Bitmap method used in the literature. Numerical results are obtained and presented in this paper.