'Institute of Electrical and Electronics Engineers (IEEE)'
Abstract
Data warehouses (DWH) have been established as the core of decision support systems. On top of a DWH, different applications can be realised with regard to conventional reporting. On line Analytical Processing (OLAP) has reached the maturity as an interactive and explorative way of analysing DWH data. However DWH are mostly organised as snapshot databases. For this reason important tasks like "how many times have products of a specific brand been sold in the "past?" cannot be answered successfully - in order to control the success of reshuffling the product range it is necessary to compare the sales of "old" and "new" products. The same applies in cases where the seasonality aspect for a particular range of products has to be answered. On the other hand, temporal databases allow a valid time to be assigned to data. In this manner, a past
state can be reconstructed during retrieval. In this paper,
we address the integration of DWH and OLAP with temporal database semantics
