Vol. 1/No. 2 (2009) INTERNETWORKING INDONESIA JOURNAL 11 ISSN: 1942-9703 / © 2009 IIJ Index Terms—Business Intelligence, Data Mining, Strategic Management. Abstract—Business Intelligence (BI) is becoming an important IT framework that can help organizations managing, developing and communicating their intangible assets such as information and knowledge. Thus it can be considered as an imperative framework in the current knowledge-based economy arena. In this paper, we will explain the role BI is playing in providing organizations with a way to plan and achieve their business strategy. We will experiment this role using a case study in the field of high education, especially helping one of the new private university in Syria (Arab International University)planning and achieving their business strategy. I. INTRODUCTION usiness Intelligence is becoming vital for many organizations, especially those have extremely large amount of data. Decision makers depend on detailed and accurate information when they have to make decisions. BI can provide decision makers with such accurate information, and with the appropriate tools for data analysis. BI is an umbrella term that combines architectures, tools, data bases, applications, practices, and methodologies [20, 6]. Gartner Group (1996) (the first company used BI in marker in the mid-1990) defined BI as “information and applications available broadly to employees, consultants, customers, suppliers, and the public. The key to thriving in a competitive marketplace is staying ahead of the competition. Making sound business decisions based on accurate and current information takes more than intuition. Data analysis, reporting, and query tools can help business users dig in the mine of data to extract and/or synthesize valuable information from it – today these tools collectively fall into category called Business Intelligence” [9]. Many organizations who developed successful BI solutions, such as Continental Airlines, have seen investment in BI generate increases in revenue and cost saving equivalent to 1000% return on Manuscript received September 30, 2009. Mouhib Alnoukari is with the Arab International University, Damascus, Syria (phone: +963-015-2050; fax: +963-015-860385; e-mail: m- noukari@aiu.edu.sy). investment (ROI) [22]. An important question that was raised by many researchers [16, 18] as to what was the main reason pushing companies to search for BI solutions, and what differentiates BI from Decision Support System (DSS) systems? In fact, over the last decades, organizations developed a lot of Operational Information Systems (OIS), resulting in a huge amount of disparate data that are located in different geographic locations, on different storage platforms, with different forms. This situation prevents organization from building a common, integrated, correlated, and immediate access to information at its global level. DSS evolved during the 1970s, with the objective of providing organization’s decision makers with the required data to support decision-making process. In the 1980s, Executive Information System (EIS) evolved to provide executive officers with the information needed to support strategic decision-making process. BI evolved during the 1990s as data-driven DSS, sharing some of the objectives and tools of DSS and EIS systems. BI architectures include: data warehousing, business analytics, business performance management, and data mining. Most of BI solutions are dealing with structured data [1]. However, many application domains require the use of unstructured data (or at least semi-structured data), e.g. customer e-mails, web pages, competitor information, sales reports, research paper repositories, and so on [4, 21]. Any BI solution can be divided into the following three layers [1]: data layer, which is responsible for storing structured and unstructured data for decision support purposes. Structured data is usually stored in Operational Data Stores (ODS), Data Warehouses (DW), and Data Marts (DM). Unstructured data are handled by using Content and Document Management Systems. Data are extracted from operational data sources, e.g. SCM, ERP, CRM, or from external data sources, e.g. market research data. Data are extracted from data sources that are transformed and loaded into DW by ETL tools. Logic layer provides functionality to analyze data and provide knowledge. This includes OLAP, data mining. And finally access layer, realized by some sort of software portals (BI portal). Our main focus in this paper is to explain the role of BI solution that helps organizations in formulating, Using Business Intelligence Solutions for Achieving Organization’s Strategy: Arab International University Case Study Mouhib Alnoukari Arab International University, Damascus, Syria B