Another twist on the prior example is to use the value in more than one column to determine whether a specific column value is valid.
For instance, say I want to ensure that when I enter an Hourly Salary Type, I want the Salary to be less than 0.00 or when Monthly Salary Type is entered the Salary is not over ,000, and when an Annual Salary Type is enter then any Salary amount is fine.
For instance, if I wanted to create a single constraint that checked both the Salary, and Salary Type constraints I created above I could use the following code: This single constraint does the same thing as the above two constraints.
Keep in mind when you do this it will be more difficult to understand whether it was the Salary Type, Salary, or both columns that violated your check constraint.
When either one of these conditions in the check constraint evaluates to FALSE a row will not be inserted, or updated in the Payroll table, and an error message will be displayed.
If you want create a table level check constraint you can run this code: Here I have created a single table constraint that checks Salary column, but instead of associating it with the column, I associated it with the table.
Data validation is a critical part of your application to ensure your data meets the requirements developed by your business analysts.