A Proposed Quality Assurance Intelligent Model for Higher Education Institutions in Saudi Arabia Abdelmonim M. Artoli, Hassan I. Mathkour, and Alaaeldin M. Hafez College of Computer and Information Systems , King Saud University Saudi Arabia Emails: binmathkour@yahoo.com, aartoli@ksu.edu.sa, ahafez@ksu.edu.sa Abstract. Recent growth and demands for dealing with increasing complexity in management, evaluation and accreditation of higher educational institutions have led keynote academic institutions and higher education authorities to adopt and try nonconventional solutions known to business firms to account for massive data management. The development in new practices and emerging technology for analytics and information management have offered different solutions such as data warehousing, big data and business intelligence. Such solutions are gradually being installed in a number of renown universities. Due to the difference between the two firms (higher education and buisness industry) in nature and aims, tailor-made soultions are needed. This paper shares authors’ experience in designing and implementing an educational information system in the College of Computers and Information systems at King Saud University, Saudi Arabia. The paper also highlights differences between educational intelligence and business intelligence systems. Higher education implementation aspects ensuring suitable data query service to ease the running of high educational institutions are discussed and recognized. Keywords: Higher Education Information Systems, Educational Intelligence, Business Intelligence, Data Warehousing cloud computing. 1. Introduction Business Intelligence is a concept of applying a set of technologies to turn data into meaningful information [1]. In higher educational institutions, huge amount of data is produced on daily basis. This has raised high demand for devising intelligent solutions that could handle documenting, retrieving and analyzing of highly complex data clusters. The set of technologies used in educational institutions to account for data management are similar to those used by business firms, such as Big Data, data warehouses and OLAP tools. However, certain concerns at the planning level need to be considered and case-specific solutions are unavoidable.