Data Driven vs. Metric Driven Data Warehouse Design

Author:

Artz John M.1

Affiliation:

1. The George Washington University, USA

Abstract

Although data warehousing theory and technology have been around for well over a decade, they may well be the next hot technologies. How can it be that a technology sleeps for so long and then begins to move rapidly to the foreground? This question can have several answers. Perhaps the technology had not yet caught up to the theory or that computer technology 10 years ago did not have the capacity to delivery what the theory promised. Perhaps the ideas and the products were just ahead of their time. All these answers are true to some extent. But the real answer, I believe, is that data warehousing is in the process of undergoing a radical theoretical and paradigmatic shift, and that shift will reposition data warehousing to meet future demands.

Publisher

IGI Global

Reference15 articles.

1. Artz, J. (2003). Data push versus metric pull: Competing paradigms for data warehouse design and their implications. In M. Khosrow-Pour (Ed.), Information technology and organizations: Trends, issues, challenges and solutions. Hershey, PA: Idea Group Publishing.

2. A relational model of data for large shared data banks

3. Codd, E. F. (1985, October 14). Is your DBMS really relational? Computerworld.

4. Date, C. J. (2004). An introduction to database systems (8th ed.). Addison-Wesley.

5. Fetzer, J., & Almeder, F. (1993). Glossary of epistemology/philosophy of science. Paragon House.

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