Automatic Detection of Structural Changes in Data Warehouses
Abstract
Data Warehouses provide sophisticated tools for analyzing complex data online, in particular by aggregating data along dimensions spanned by master data. Changes to these master data is a frequent threat to the correctness of OLAP results, in particular for multi- period data analysis, trend calculations, etc. As dimension data might change in underlying data sources without notifying the data warehouse, we are exploring the application of data mining techniques for detecting such changes and contribute to avoiding incorrect results of OLAP queries.
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- Eder, Johann
- Koncilia, Christian
- Mitsche, Dieter
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Copyright Holders
- © 2003 Springer Verlag (<a href='http://www.springer.de/comp/lncs/index.html'>WWW</a>)
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Shortfacts
Category |
Paper in Conference Proceedings or in Workshop Proceedings |
Event Title |
5th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2003) |
Divisions |
Workflow Systems and Technology |
Event Location |
Prague, Czech Republic |
Event Type |
Conference |
Event Dates |
2003-09-03 |
Series Name |
Lecture Notes in Computer Science 2737 |
Publisher |
Springer Verlag |
Page Range |
pp. 119-128 |
Date |
September 2003 |
Official URL |
http://www.pri.univie.ac.at/Publications/2003/Eder... |
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