402 Web Based Data Warehouse in the Egyptian Cabinet Information and Decision Support Center Hoda Ahmed Abdel Hafez* Sherif Kamel** *Faculty of Computers & Informatics Suez Canal University Egypt E-mail: hoda_hafez@yahoo.com **School of Business, Economics and Communication The American University in Cairo Egypt E-mail: skamel@aucegypt.edu Abstract This paper discusses data warehouse in the Cabinet of Egypt Information and Decision Support Center (IDSC) as one of the smart organizations in the Arab world. The case study includes the background of the IDSC, its objectives, services, initial project, and beneficiaries. It also illustrates how to build the data warehouse, problems founded during the project, the benefits of data warehouse and the lessons learned from this case. Keywords Data warehouse, online analytical processing, relational online analytical processing, decision support, information, Egypt, IT in developing nations. 1. INTRODUCTION Data warehousing is one of the new concepts that support the corporations in an uncertain world. Its systems are still complex and costly, but when they are designed, built, and operate in the right way, they can deliver a competitive advantage (Whiting, 2003). The aim of the data warehouse is to provide information at the right time, in the right place and in the right form (Imhoff and Geiger, 2001). This is usually important and invaluable for decision makers. Data warehousing is a process, not a product, for assembling and managing data from various sources for the purpose of gaining a single, detailed view of a part or all of a business (Gardnern, 1998). It is a computing environment where users can find strategic information. It is a user centric environment where users are put directly in touch with the data to help them make better decisions (Ponniah, 2001). The data warehouse includes extracting data from source systems, to be transformed and stored in order to provide user interfaces for easy access (Wixom and Watson, 2001; Ponniah, 2001). A data warehouse itself can not create value; value comes from the use of the data in the warehouse (Gary and Watson, 1997). The fundamental reason for building a data warehouse is to provide decision support applications' users with access to data warehouse; it can also be used to support queries, decision support systems, executive information systems, and data mining (Watson et al., 1998; Watson and Haley, 1998; Blaba, 2001). Data warehouse has succeeded because it fulfilled a very basic set of needs for information that every corporation had (Inmon, 2001). Data warehouse provides integrated data across all applications so that a truly corporate view of information can be made. It also contains a robust amount of history to meet both current and historical information, and holds both detailed and summary data to create the management perspectives. On-Line Analytical Processing (OLAP) is a highly specialized technology that presents information in a multidimensional format and it is designed to provide more powerful analytical capabilities than SQL (Max, 2003). OLAP always involves interactive querying of data, following a thread of analysis through multiple passes and also provides modeling capabilities including a calculation engine for deriving results and creating aggregation and consolidations (Raden, 1995). The case study tries to illuminate a decision or set of decisions: why they were taken, how they were implemented and identify the results. It is a way of investigating an empirical topic by following a set of pre- specified procedures. It is a descriptive case study, which covers various sections such as an organization’s history, its ownership and employees, its formal lines of organizations, and its product lines (Yin, 1994).