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A Survey of Managing the Evolution of Data Warehouses
Abstract
Methods of designing a data warehouse (DW) usually assume that its structure is static. In practice, however, a DW structure changes among others as the result of the evolution of external data sources and changes of the real world represented in a DW. The most advanced research approaches to this problem are based on temporal extensions and versioning techniques. This article surveys challenges in designing, building, and managing data warehouses whose structure and content evolve in time. The survey is based on the so-called Multiversion Data Warehouse (MVDW). In details, this article presents the following issues: the concept of the MVDW, a language for querying the MVDW, a framework for detecting changes in data sources, a structure for sharing data in the MVDW, index structures for indexing data in the MVDW.
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