Data transformation (computing): Difference between revisions

Revision as of 04:32, 28 September 2020

Revision as of 20:05, 28 July 2021

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Data transformation can be simple or complex based on the required changes to the data between the source (initial) data and the target (final) data. Data transformation is typically performed via a mixture of manual and automated steps.<ref name="livinglab.mit.edu">DataXFormer. Morcos, Abedjan, Ilyas, Ouzzani, Papotti, Stonebraker. An interactive data transformation tool. Retrieved from: http://livinglab.mit.edu/wp-content/uploads/2015/12/DataXFormer-An-Interactive-Data-Transformation-Tool.pdf</ref> Tools and technologies used for data transformation can vary widely based on the format, structure, complexity, and volume of the data being transformed.

A [[master data]] recast is another form of data transformation where the entire [[database]] of data values is transformed or recast without extracting the data from the database. All data in a well designed database is directly or indirectly related to a limited set of master [[database table]]s by a network of [[foreign key]] constraints. Each foreign key constraint is dependent upon a unique [[database index]] from the parent database table. Therefore, when the proper master database table is recast with a different unique index, the directly and indirectly related data are also recast or restated. The directly and indirectly related data may also still be viewed in the original form since the original unique index still exists with the master data. Also, the database recast must be done in such a way as to not impact the [[applications architecture]] software.

When the data mapping is indirect via a mediating [[data model]], the process is also called '''data mediation'''.