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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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