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Session 2358

University Data Warehouse Design Issues: A Case Study

Melissa C. Lin

Chief Information Office, University of Florida

Abstract

A discussion of the design and modeling issues associated with a data warehouse for the University of Florida, as developed by the office of the Chief Information Officer (CIO). The data warehouse is designed and implemented on a mainframe system using a highly de-normalized DB2 repository for detailed transaction data and for feeding data to heterogeneous data models owned by different administrative units. The details of technology selection, business requirements, tools building, cultural challenges, architecture modes, models, and hardware information will be described. The data warehouse analysis, logical and physical design, application server, and implementation issues will also be explained.

I. Introduction

The computing and data service environment at the University of Florida is large and diverse. It was formed within the numerous political and funding boundaries of the past several decades. The advancement of new technologies and the need for quick access to up-to-date student and employee data have put great pressure on the university to develop and to maintain a central database for administrative use. The data warehouse project had to utilize existing computing facilities and databases, bringing them together and using their strengths in new ways. The Office of the CIO had to create a data warehouse that supported all administrative units and provided easy, timely, accurate access to the information maintained by key administrative offices across campus. These offices include the Office of Information Systems, the Office of the University Registrar, the Dean of Students Office, the International Student Center, Student Financial Affairs, the Health Science Center, Academic Advising Center, University Libraries, the Graduate School and others.

Our data warehouse is a central, logical site that stores many data models, supports central management’s priorities, and complements the university’s business needs. It facilitates a broad scope of tasks, such as: • Extracting data from legacy systems and other data sources, • Cleansing, scrubbing, and preparing data for decision supports,

Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright  2001, American Society for Engineering Education

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Lin, M. (2001, June), University Data Warehouse Design Issues: A Case Study Paper presented at 2001 Annual Conference, Albuquerque, New Mexico. 10.18260/1-2--9936