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XML in a Data Warehouse Design: Performance Evaluation Utilizing Geological Data

XML in a Data Warehouse Design: Performance Evaluation Utilizing Geological Data
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Author(s): Behrooz Seyed-Abbassi (University of North Florida, USA) and Lori Stowers Pusey (University of North Florida, USA)
Copyright: 2007
Pages: 5
Source title: Managing Worldwide Operations and Communications with Information Technology
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-929-8.ch050
ISBN13: 9781599049298
EISBN13: 9781466665378

Abstract

The structure of XML data presents challenges when determining efficient ways to map it to a relational data warehouse. One of these challenges is the presence of multi-valued child elements. Translating multi-valued XML elements to a relational data warehouse may require the consideration of non-traditional approaches to the design of the data warehouse. Traditionally, the star schema has been the design of choice for data warehouses. However, the semi-structured nature of XML data may make the use of alternatives, such as the snowflake schema, more efficient. This paper presents the implementation details of methods for preserving XML data in a relational data warehouse that are based on the star and snowflake design schemas and compares the methods quantitatively and qualitatively.

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