Data validity is the correctness and reasonablenesss of data. Reasonableness of data means that, for example, account numbers falling within a range, numeric data being all digits, dates having a valid month, day and year, and spelling of proper names. Data validity errors are probably the most common, and most difficult to detect (data-related) errors.

What causes data validity errors? Data validity errors are usually caused by incorrect data entries, when a large volume of data is entered in a short period of time. For example, a data entry operator enters 12/25/2010 as 13/25/2010, by mistake, and this data is therefore invalid. How can you reduce data validity errors? You can use one of the following two, simple field validation techniques.

Technique 1: If the date field in a database uses the MM/DD/YYYY format, then you can use a program with the following two data validation rules: "MM" should not exceed "12", and "DD" should not exceed "31".

Technique 2: If the original figures do not seem to match the ones in the database, then you can use a program to validate data fields. You can compare the sum of the numbers in the database data field to the original sum of numbers from the source. If there is a difference between the two figures, it is an indication of an error in at least one data element.