Using these data definitions, a range of software validation checks can be carried out.
Consistency check ensures that the entered data is logical.
For example, many database systems allow the specification of the following l (plus, minus, and parentheses).
A more sophisticated data validation routine would check to see the user had entered a valid country code, i.e., that the number of digits entered matched the convention for the country or area specified.
The difference between data validity and accuracy can be illustrated with a trivial example.
A company has established a Personnel file and each record contains a field for the Job Grade. An entry in a record may be valid and accepted by the system if it is one of these characters, but it may not be the correct grade for the individual worker concerned.
A judgement as to whether data is valid is made possible by the validation program, but it cannot ensure complete accuracy.
For example, an experienced user may enter a well-formed string that matches the specification for a valid e-mail address, as defined in RFC 5322 but that well-formed string might not actually correspond to a resolvable domain connected to an active e-mail account.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, Data validation is intended to provide certain well-defined guarantees for fitness, accuracy, and consistency for any of various kinds of user input into an application or automated system.Data validation rules can be defined and designed using any of various methodologies, and be deployed in any of various contexts.