Enterprise application integration with XML and Java
Enterprise application integration with XML and Java
C#: How to Program
CPI: constraints-preserving inlining algorithm for mapping XML DTD to relational schema
Data & Knowledge Engineering - ER2000
XML Data Management: Native XML and XML Enabled DataBase Systems
XML Data Management: Native XML and XML Enabled DataBase Systems
Xyleme: A Dynamic Warehouse for XML Data of the Web
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
XQuery from the Experts: A Guide to the W3C XML Query Language
XQuery from the Experts: A Guide to the W3C XML Query Language
XML Primer Plus
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Information Systems Reengineering and Integration
Information Systems Reengineering and Integration
Improving data quality through effective use of data semantics
Data & Knowledge Engineering - Special issue: WIDM 2004
XML-OLAP: a multidimensional analysis framework for XML warehouses
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Querying sensor data for environmental monitoring
International Journal of Sensor Networks
Semantic similarity measurement using historical google search patterns
Information Systems Frontiers
Topological XML data cube construction
International Journal of Web Engineering and Technology
| Hi-index | 0.01 |
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.