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Denormalization
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{{Refimprove|date=May 2008}} {{short description|Strategy used on previously-normalized databases}} '''Denormalization''' is a strategy used on a previously-[[Database normalization|normalized]] database to increase performance. In [[computing]], denormalization is the process of trying to improve the read performance of a [[database]], at the expense of losing some write performance, by adding [[Redundancy (information theory)|redundant]] copies of data or by grouping data.<ref>G. L. Sanders and S. K. Shin. [https://web.archive.org/web/20171201030308/https://pdfs.semanticscholar.org/2c79/069c01ba8d598f32e61fe367ef6d261a0cb4.pdf Denormalization effects on performance of RDBMS]. In Proceedings of the HICSS Conference, January 2001.</ref><ref>S. K. Shin and G. L. Sanders. [http://portal.acm.org/citation.cfm?id=1217757 Denormalization strategies for data retrieval from data warehouses]. Decision Support Systems, 42(1):267-282, October 2006.</ref> It is often motivated by [[Computer performance|performance]] or [[scalability]] in [[relational model|relational]] [[DBMS|database software]] needing to carry out very large numbers of read operations. Denormalization differs from the [[unnormalized form]] in that denormalization benefits can only be fully realized on a data model that is otherwise normalized.
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