Abstract
Like all software systems, databases are subject to evolution as time passes. The impact of this evolution is tremendous as every change to the schema of a database affects the syntactic correctness and the semantic validity of all the surrounding applications and de facto necessitates their maintenance in order to remove errors from their source code. This survey provides a walk-through on different approaches to the problem of handling database and data warehouse schema evolution. The areas covered include (a) published case studies with statistical information on database evolution, (b) techniques for managing schema and view evolution, (c) techniques pertaining to the area of data warehouses, and, (d) prospects for future research.
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Manousis, P., Vassiliadis, P., Zarras, A., Papastefanatos, G. (2016). Schema Evolution for Databases and Data Warehouses. In: Zimányi, E., Abelló, A. (eds) Business Intelligence. eBISS 2015. Lecture Notes in Business Information Processing, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-319-39243-1_1
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