Academic journal article Journal of Information Systems Education

Teradata University Network: A No Cost Web-Portal for Teaching Database, Data Warehousing, and Data-Related Subjects

Academic journal article Journal of Information Systems Education

Teradata University Network: A No Cost Web-Portal for Teaching Database, Data Warehousing, and Data-Related Subjects

Article excerpt

1. INTRODUCTION

Database management, one of the standard subjects taught worldwide in Information systems (IS) curricula, is an expanding field. New topics are continually being added, including data warehousing, large-scale databases, on-line analytical processing (OLAP), business intelligence (BI), and data mining. These additions recognize and facilitate the use of data to support decision-making. Although each of these topics could merit a course of its own, most colleges and universities are able to add at most one elective in these new areas. On the other hand, graduates are increasingly expected to demonstrate not only knowledge of established and routinely used database concepts but also the new data management and analysis methods.

In this paper we describe and discuss a comprehensive academic initiative, the Teradata University Network (TUN), that gives IS faculty access to resources for providing their students with needed knowledge. As shown in the sidebar, what is unique about this initiative is that it is without cost to the institution, the faculty, and the students.

What makes TUN valuable and viable is that an academic working group, representing the faculties in over 850 universities in 69 countries that use the network, implements TUN's mission statement: "To be a premier academic resource for knowledge about data warehousing, DSS/BI, and data. To build an international community whose members share their ideas, experiences, and resources with one another. To serve as a bridge between academia and the world of practice."

This paper is organized as follows. To put the capabilities of TUN into context, we provide a brief overview of traditional and emerging data management and analysis topics being covered in contemporary IS related education in Section 2. In Section 3 we introduce resources available in the Teradata University Network in both traditional and emerging areas. Section 4 explains the capabilities available to students in the Teradata Student Network. Section 5 examines the benefits and value of using the portal for various constituencies within the IS education process. The major differences between TUN and other initiatives in this area are highlighted in the concluding section (Section 6). In addition, Appendix 1 explains how simple it is for faculty to join the TUN network.

THE ECONOMICS OF THE TERADATA
UNIVERSITY NETWORK

Most, if not all of us, usually ignore "no cost" offers from
software vendors because we learned long ago that there is
no "free lunch". But the Teradata University Network is an
exception. In 2001, Teradata agreed to a proposal from
Prof. Jeff Hoffer of the University of Dayton, Prof. Hugh
Watson of the University of Georgia, and Prof. Barbara
Wixom of the University of Virginia to allow faculty and
students access to their large database computing
resources. Access was a remarkable gift to academia. In the
years since then, other firms such as MicroStrategy, with
its business intelligence capabilities, also made their
software available at no cost.

Not only are access to the software and use of
teaching materials provided, no other costs are incurred.
Because access is through the World Wide Web in a
"Software as a Service" arrangement, no installation,
updating, administering, and maintenance costs are
incurred by schools. Multi-million record data sets are
made available by Teradata's partner-organizations.
Teaching aids and materials, including student exercises,
homework assignments, articles, and cases are contributed
by faculty who use the network. No storage is used at the
institution's data center for the software or the databases.

2. THE REACH OF DATA

There's much more to teaching about data than just defining databases as relational, hierarchical, or flat. This section describes data subjects that can occupy from a single class session to one or more full courses. …

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