Denormalization Strategies for Data Retrieval from Data Warehouses

Decision Support Systems, Vol. 42, No. 1, pp. 267-282, 2006

Posted: 12 Feb 2008

See all articles by Seung Kyoon Shin

Seung Kyoon Shin

The University of Rhode Island

G. L. Sanders

SUNY at Buffalo - School of Management; State University of New York (SUNY) - Management Science and Systems

Abstract

In this study, the effects of denormalization on relational database system performance are discussed in the context of using denormalization strategies as a database design methodology for data warehouses. Four prevalent denormalization strategies have been identified and examined under various scenarios to illustrate the conditions where they are most effective. The relational algebra, query trees, and join cost function are used to examine the effect on the performance of relational systems. The guidelines and analysis provided are sufficiently general, and they can be applicable to a variety of databases in particular to data warehouse implementations for decision support systems.

Keywords: Database Design, Denormalization, Decision Support Systems, Data Warehouse, Data Mining

Suggested Citation

Shin, Seung Kyoon and Sanders, G. Lawrence, Denormalization Strategies for Data Retrieval from Data Warehouses. Decision Support Systems, Vol. 42, No. 1, pp. 267-282, 2006, Available at SSRN: https://ssrn.com/abstract=1091613

Seung Kyoon Shin

The University of Rhode Island ( email )

7 Lippitt Road
Kingston, RI 02881
United States
401-874-5543 (Phone)

G. Lawrence Sanders (Contact Author)

SUNY at Buffalo - School of Management ( email )

Jacobs Management Center
Buffalo, NY 14222
United States

State University of New York (SUNY) - Management Science and Systems ( email )

United States

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