Analysis of the Role of Data Warehouse in Higher Education

Document Type : Original Article

Authors

Abstract

Executive, tactical and strategic decisions are common in any organization. At all three levels, examples of data are found and can become useful tools to support their decision. Higher education is also one of the parts that can benefit from data warehouse. The objective of this research is to examine the use of data warehousing in higher education  decision-making and to compare the types of data in data warehouse that are provided by various higher education institutes. In this paper, a description - analytic method is used. In the first part of this article, the concepts of data warehouse and its application in decision-making is expressed. Next, the data warehouse architecture which should be considered in designing a data warehouse is explained. In the next section, analytical comparison among data warehouses of different higher education institutes have been done, and finally we have recommended parts of a data warehouse that can be used and is suitable for most universities. The general findings of the study show different higher education centers use various data marts with different kinds of information because of information needs of users, but they are common in some provided data.

Keywords


ادیبی، ژینوس (1387). چارچوب ارزیابی قابلیت سازمان برای پیاده‌سازی انبار داده. پایان‌نامة کارشناسی ارشد مدیریت فنّاوری اطلاعات، دانشگاه الزهرا (س).
کاهانی، محسن (1381). طراحی سیستم جامع اطلاعات و MIS دانشگاه فردوسی مشهد، جلد 2. مرکز کامپیوتر، آمار و اطلاعات دانشگاه.
یثربی، احسان (1382). طراحی و پیاده‌سازی انبارة داده مرکزی تحت وب. پایان‌نامة کارشناسی ارشد گروه کامپیوتر دانشگاه فردوسی مشهد.
 
Bain, T., Benkovich, M., Dewson, R., Ferguson, S., Graves, C., Joubert, T.J., Lee, D., Scott, M., Skoglund, R., Turley, P and Youness, S. (2001). Professional SQL Server 2000 Data Warehousing with Analysis Service. Wrox Press, Birmingham, United Kingdom.
Distefano, J. (1999). The decisioning frontier: Blending history, experience and intuition. DM Review, 9, p. 14.
Foley, J. (1997). Data warehouse pitfalls. InformationWeek, (631), 93-96. http://search.proquest.com/docview/229057199?accountid=45209
Gartner, J., Maberry, S., & O’Connell, W. (2005). Data Warehouse Software Maintenance Strategy. IBM Corporation.
Guan, J., Nunez, W., & Welsh, J. F. (2002). Institutional strategy and information support: the role of data warehousing in higher education. Campus-Wide Information Systems, 19(5), 168 - 174.
Heise, D. L. (2006). Data warehousing and decision making in higher education in the United States. Ph.D. 3209766, Andrews University, United States -- Michigan. Retrieved from http://search.proquest.com/docview/304959463?accountid=45209 ABI/INFORM Global; ProQuest Dissertations & Theses (PQDT) database.
Hwang, H.G., Ku, C.Y., Yen, D.D. and Cheng, C.C. (2004). Critical factors influencing the adoption of data warehouse technology: a case study of the banking industry in Taiwan. Decision Support Systems, (37), 1-21.
Inmon, W. H. (1996). Building the data warehouse: Wiley & Sons Inc., New Tork, NY.
Massy, W. F., & Wilger, A. K. (1998). Technology's contribution to higher education productivity. New Directions for Higher Education, 26(3), 49-59.
Oregon State University (2012). OUS/OSU Data Warehouse. Retrieved February 3, 2012, from http://oregonstate.edu/dept/computing/warehouse/
Tanler, R. (1997). The Intranet Data Warehouse, New York: John Wiley & Sons, Inc.
Turban, E., Aronson, J. E., & Liang, T.-P. (2004). Decision Support Systems and Intelligent Systems (7th edition ed.): Prentice-Hall.
UC Santa Cruz (2012). UCSC Data Management Services. Retrieved December 29, 2011, from http://planning.ucsc.edu/datamgmt/default.htm
University of California San Diego (2012). Data Warehouse. Retrieved February 16, 2011, from blink.ucsd.edu/technology/help-desk/queries/warehouse/index.html

University of Illinois (2012). Decision Support. Retrieved January 21, 2012, from http://www.ds.uillinois.edu/web/

University of Miami (2012). Data Warehouse System. Retrieved January 25, 2012, from http://www.miami.edu/index.php/hr/HR_systems /UMSYS/other_systems/data_warehouse_system/
University of Pennsylvania (2012). Pennsylvania Data Warehouse. Retrieved January 9, 2012, from http://planning.ucsc.edu /datamgmt/dwh/
Walker, D. M. (2010). Resolving Data Warehousing Challenges through Modeling. Data Management, 12. 
Watson, H. J., & Ariyachandra, T. (2005). Data Warehouse Architectures: Factors in the Selection Decision and the Success of the Architectures, Technical Report, Terry College of Business, University of Georgia, Athens, GA.
Weber, R. P., & Weber, J. E. (2000). The Use and Value of Data Warehousing in Higher Education. Mountain Plains Journal.