Systematic Change Management in Dimensional Data

Design and maintenance of data warehouses has become an important research topic. In parallel to this, the topic of temporal databases is also an active area of research. This article covers the application of temporal ideas to data warehouse design. First, we present the notion of a data warehouse in general and describe the most approved method of structuring data in data warehouses, namely star schemas. Then we point to two star schema problems related to management of changing information|handling of slowly changing dimensions and state-oriented data. We present a rather new approach to data modelling in data warehouses, so-called temporal star schemas, that is a solution to the mentioned problems. In the literature, it is claimed that temporal star schemas can store more data in less space and make queries on the data faster, in comparison to regular star schemas. The comparison of instances of both schemas according to the size and query performance is the main topic of this article. The comparison is based on a speciic case and aims to cover state-oriented data. Based on our experience, we conclude the article sharing some impressions about the ease of understanding and querying data in the temporal and regular star schemas.