Validity

Data is valid if it conforms to a specific syntax or rules. For data to be valid, it should be collected according to predefined rules and parameters, and should conform to the right format and be within the right range to be valid.
Various Definitions: 
Data values are consistent with a predefined domain of values like controlled pick-list or reference data values for example : ISO-3166. 
Data is valid if it conforms to the syntax (format, type, range) of its definition. For example, Date format DD-MM-YYYY 
Data is valid if it conforms to defined business rules. For example, cancelation date < travel date Conformance of data to the structure of data. 
Measuring Validity
All data can typically be measured for Validity. Validity applies at the data item level, record level (for combinations of valid values), as well as metadata. 
Unit of Measure: Percentage of data items valid. 
Related dimensions: Accuracy, Completeness, Consistency and Uniqueness
Notes Data may also be valid only for a specific length of time. For example data that is generated from RFID or scientific datasets.
Last modified 1yr ago