Data Validation

Data Validation is the process of ensuring that the data has undergone data cleaning to assure the data quality, and making sure that the data is correct and useful. The processes within Data Validation are validation rules, validation constraints, and check routines. These processes check the data for its correctness, meaningfulness, and secureness before it is inputted to the system. Data Validation may be implemented through automation (data dictionary), or by the inclusion of application program with validation logic.

Data Validation is intended to provide certain well-guarantees for fitness and consistency of the data in a certain system. The rules within can be defined using several methods and may be deployed in various contexts. The major implementation of Data Validation are through Data Integrity rules and Procedure-based Business rules.

Data Validation do not necessarily guarantee its accuracy and it is possible for data entry errors to be accepted as valid. Data Validation cannot be confused with Data Verification.

Data Validation Types

There are several types depending on the different kinds of validation according to their scope, complexity, and purpose.

Data-type Check

Data type validation typically done on simple data fields. The simplest approach is to make sure every characters from a user input are consistent with the expected characters of specific known data types as intended. For example, an integer field can be set to only accept characters from 0 to 9.

Range and constraint Check

Range and constraint validation examine user inputt for consistency with maximum/minimum range or consistency with a test for a sequence of characters. For example, a password is required to meet a minimum length and must contain characters from multiple groups (alphabets, numerical, special characters).

Code and cross-reference Check

Code and cross-reference validation verify the consistency of the data with one or more rules, requirements, or collections relevant to a certain context or set of assumptions. For example, a user-provided country code might be required to identify a geopolitical region.

Structured Check

Structured validation combines several others validation, usually it is on a more complex system.

Consistency Check

Consistency validation ensure the logicality of the data. For example, expiry date of a document cannot precedes its starting date.

Data Validation Methods

• Allowed Characters Check
• Batch Totals
• Cardinality Check
• Check Digits
• Consistency Check
• Cross-system Consistency Check
• Data Type Check
• File Existence Check
• Format Check
• Presence Check
• Range Check
• Referential Integrity Check
• Spelling and Grammar Check
• Uniqueness Check
• Table-look Check