Data validation: Difference between revisions

Revision as of 14:59, 23 September 2019

Revision as of 13:53, 4 October 2019

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{{more citations needed|date=November 2016}}

In [[computer science]], '''data validation''' is the process of ensuring [[data]] have undergone [[data cleansing]] to ensure they have [[data quality]], that is, that they are both correct and useful. It uses routines, often called "validation rules" "validation constraints" or "check routines", that check for correctness, meaningfulness, and security of data that are input to the system. The rules may be implemented through the automated facilities of a [[data dictionary]],<ref>{{Cite web|url=|title=Data dictionary|last=|first=|authorlink=|last2=|authorlink2=|date=|website=|publisher=video 18+|others=|archive-url=|archive-date=|dead-url=|access-date=}}</ref> or by the inclusion of explicit [[application program]] validation logic.

==Overview ==

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===Post-validation actions===

{{refimproveMore citations needed section|date=July 2012}}

;Enforcement Action

:Enforcement action typically rejects the data entry request and requires the input actor to make a change that brings the data into compliance. This is most suitable for interactive use, where a real person is sitting on the computer and making entry. It also works well for batch upload, where a file input may be rejected and a set of messages sent back to the input source for why the data is rejected.

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==Validation and security==

Failures or omissions in data validation can lead to [[data corruption]] or a [[soasp/html/ch10.html Chapter10. Data Validation]]</ref> Data validation checks that data are fit for purpose,<ref>[https://web.archive.org/web/20171201042621/https://spotlessdata.com/blog/more-efficient-data-validation-spotless More Efficient Data Validation with Spotless]</ref> valid, sensible, reasonable and secure before they are processed.

== See also ==