By using validation rules, you can ensure accurate data entry (to a point).Validation rules catch errors at the data entry level, so in effect, the mistakes never make it into your database.Only when the hours worked value equals 40, do you want the overtime field to accept an Integer greater than 0.In this case, you'd use a record-level validation rule, which is actually a table property that you can set as follows: To protect the validity of your data, you start at the foundation.These rules are generally defined in a data dictionary or are implemented through data validation software.
It checks for the integrity and validity of data that is being inputted to different software and its components. All sections should be reviewed The most common web application security weakness is the failure to properly validate input from the client or environment.Data from the client should never be trusted for the client has every possibility to tamper with the data.Data validation ensures that the data complies with the requirements and quality benchmarks. Data validation primarily helps in ensuring that the data sent to connected applications is complete, accurate, secure and consistent.This is achieved through data validation's checks and rules that routinely check for the validity of data.(Use the Validation Text property to display a custom message when the data doesn't satisfy the validation rule.) Keep in mind that validation rules can't prevent all input errors.For instance, an employee who works 23 hours might transpose the digits and enter 32—there's no rule that's going to catch that error.Protecting the validity of your data is one of the most important tasks of a database developer.To ensure that users enter accurate data, start at the foundation.You can apply a validation rule to a field or to a record.At the field level, the rule checks the data for only the field constrained by the rule.