Automatic Detection of Structural Changes in Data Warehouses

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 are 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.

• Type: Conference
• Year: 2003
• Where: DAWAK
• Authors: Johann Eder, Christian Koncilia, Dieter Mitsche
• Keywords: Complex Data Online, Data Mining, Data Warehouse, DAWAK 2003, Master Data