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Building OLAP Cubes on XML Data (Abstract)
On-Line Analytical Processing (OLAP) enables analysts to gain insight into data through fast and interactive access to a variety of possible views on information, organized in a dimensional model. The demand for data integration is rapidly becoming larger as more and more information sources appear in modern enterprises. In the traditional data warehousing approach, selected information is extracted in advance and stored in a repository. This approach is widely adopted because of its high-performance guarantee. However, in some situations a logical (rather than a physical) integration of data is preferable since some data is inherently not suited for storing in a data warehouse, e.g. dynamically evolving information.

Extensible Markup Language (XML) is fast becoming the new standard for data representation and exchange on the World Wide Web. The rapid emergence of XML data on the Web, e.g. business-to-business (B2B) e-commerce, is making it necessary for OLAP and other data analysis tools to handle XML data as well as traditional data formats.

Based on a real-world case study, this paper presents an approach to the conceptual specification of OLAP DBs based on both relational data and XML data on the web. Unlike previous work, this approach takes special OLAP issues such as dimension hierarchies and correct aggregation of data into account. We present a new conceptual model for designing OLAP DBs from multiple, heterogeneous data sources and describe how queries are efficiently processed. Additionally, an integration architecture that allows the logical integration and querying of XML and relational data sources for use by OLAP tools is presented.

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Most Downloaded Publications
Specifying OLAP Cubes On XML Data, Journal Edition (PDF)
Converting XML Data to UML Diagrams for Conceptual Data Integration (PDF)
Discovering Multidimensional Structure in Relational Data (PDF)


External References
DBLP Computer Science Bibliography
The OLAP Council
Datawarehouse Tools and Tutorials
DP Research Unit, Aalborg University
ACM SIGMOD
Scientific and Statistical Database Management (SSDBM)


External References Free Math Software
GNUPlot
Scilab
Octave
R Project


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