Premium
A relational–XML data warehouse for data aggregation with SQL and XQuery
Author(s) -
Fong Joseph,
Shiu Herbert,
Cheung Davy
Publication year - 2008
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.868
Subject(s) - computer science , xquery , data warehouse , online analytical processing , xml database , streaming xml , database , relational database , sql , nosql , xml , efficient xml interchange , xml validation , xml schema editor , business intelligence , materialized view , xslt , data transformation , information retrieval , world wide web , database design , view , scalability
Integrating information from multiple data sources is becoming increasingly important for enterprises that partner with other companies for e‐commerce. However, companies have their internal business applications deployed on diverse platforms and no standard solution for integrating information from these sources exists. To support business intelligence query activities, it is useful to build a data warehouse on top of middleware that aggregates the data obtained from various heterogeneous database systems. Online analytical processing (OLAP) can then be used to provide fast access to materialized views from the data warehouse. Since extensible markup language (XML) documents are a common data representation standard on the Internet and relational tables are commonly used for production data, OLAP must handle both relational and XML data. SQL and XQuery can be used to process the materialized relational and XML data cubes created from the aggregated data. This paper shows how to handle the two kinds of data cubes from a relational–XML data warehouse using extract, transformation and loading. Copyright © 2008 John Wiley & Sons, Ltd.