It is well known that transactional and analytical systems each require different database architecture. In general, the database structure of transactional systems is optimized for consistency and efficient updates while the database structure for decision-support systems is optimized for complex query analysis and key performance indicators reporting. Spatial data has also become an important ingredient to consider in data warehouses to support spatial-temporal analysis aims. To monitor their activities and measure the performance of their procedures, today's organizations deploy data warehouses and client tools such as OLAP (On-Line Analytical Processing) to access, visualize, and analyze their integrated, aggregated and summarized data. Since a large part of these data has a spatial component, suitable tools are required to take full advantage of the geometry of the spatial phenomena or objects being analyzed. With this regard, Spatial OLAP (SOLAP) technology offers promising...
I. Salam, M. El Mohajir, A. Taleb, B. El Mohajir