Changes in transaction data are recorded in data warehouses and sophisticated tools allow to analyze these data along time and other dimensions. But changes in master data and in structures, surprisingly, cannot be represented in current data warehouse systems impeding their use in dynamic areas and/or leading to erroneous query results. We propose a temporal data warehouse architecture to represent structural changes and permit correct analysis of data over periods with changing master data. We show how typical business cases involving change in master data can be solved using this approach and we discuss architectural variants for the implementation.

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