Data validation is the process of checking the accuracy and quality of data to be used in any important business process. As the use of data for decision-making increases, proper validation methods assist in minimizing expensive mistakes and increase productivity. The following is a description of the most used data validation methods and an example of each to show the impact.
Format validation checks that input data entered in a particular system is in the correct format. This data validation technique is especially important for such fields as, for example, email addresses, phone numbers, and dates because they should have a specific format.
Example
A company’s customer relationship management (CRM) system may need phone numbers to be in the format (XXX) XXX-XXXX. If the user enters a phone number with or without parentheses or additional numerals, the system will identify it as invalid. Such validation service helps to make certain that the customer contact data is accurate and standard.
Range validation is another data validation technique which determines whether the data entered is numeric or not and if it fits into the set range or not, if it is reasonable or not.
Example
In a payroll system, the requirements may require that the age of the employees should be between 18 and 65 years. If, for instance, one attempts to input an age of 120, the system would not accept it. This data validation technique helps to exclude freak data that are not useful in reporting or in making a calculation.
Type data validation technique means that the data entered is in the right format, for example, numbers, text, or date.
Example
In a financial application, a field may expect a dollar amount. Type validation will prevent this entry if a user enters alphabetic characters into this field instead of numbers. This data validation technique is useful in making all data to be processed to be processable to avoid cases where the system hangs or the calculations are wrong.
Data uniqueness checks whether or not there is repetition in the fields that should not have repeating entries, for example, user IDs, emails, or social security numbers.
Example
Membership registration system means that each user must provide a separate email address. If two users use the same email to try to get through the registration process, the system will not allow the second person to register thereby preserving the identity of the users.
Consistency validation is used to check if certain fields have valid values within their field type; for example, date fields should not contain alphabets. For instance, related fields should not counteract one another.
Example
Suppose in an online form for registering for car loans, a user has chosen ‘sedan’ as the type of car he requires, but then he enters ‘2 doors’ in the door section, then the system will be able to point out the fact that sedans have four doors.
Presence validation checks if all the required fields have to be filled in. This data validation technique is used commonly in forms that have some fields where a message must be input to avoid adding a form where some areas are left blank.
Example
A contact form on a website may include the name, email, and message that needs to be filled. If any of these fields are left blank, the form will not be submitted but if all these fields are filled, necessary information is entered.
Cross-field validation compares the values of two or more fields to verify that their values are accurate.
Example
This data validation method is common in an HR system where a cross-field validation is the best way to make sure that the end date of an employee is always greater than or equal to the start date. If the end date is earlier, then it will become an error in the system.
It is clear that data validation is not a one-time matter but a cyclic process that needs to be undertaken time and again. Through format, range, and type data validation methods business can protect itself from mistakes that can cause losses or slow down productivity. learn more about the data validation process.