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Denormalization strategies for data retrieval from data warehouses

  • University of Rhode Island

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

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.

Original languageEnglish
Pages (from-to)267-282
Number of pages16
JournalDecision Support Systems
Volume42
Issue number1
DOIs
StatePublished - Oct 2006

Keywords

  • Data mining
  • Data warehouse
  • Database design
  • Decision support systems
  • Denormalization

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