When you think of data validation, what's the first thing that comes to your mind?
Is it, by any chance, to enter numbers when an application is expecting numbers out of you, the user?
That is the A2)=1 portion will change to A3)=1, A4)=1 and so on.
But making sure that these are implemented in the development process rather than after the program is done will help minimize the burdon of integrating data validation in your application. Essentially everything depends on the reason why you'd want to do data validation, it's degree of importance (as far as the data available to the application) and the actually type of the data as well. Let's say you're making a mortage calculation program (that will be used by professionals all over the the continent).
These are the 3 major areas where you'd want to be sure that proper data validation is applied properly.
This will only help with the rest of the application because you'll be able to cross out the data as being a cause for problem in possible errors that might slip into the application.
There's more to data validation that simply validating the data, alot more as you'll see there is alot of things that can be done to help in the data validation process.
In this document, we will cover all you'll ever need to know about data validation, what it really means, how to use it effectively and ultimately how to minimize the use of data validation while still assuring that the data is indeed valid. Data validation, as explained above, is making sure that all data (whether user input variables, read from file or read from a database) are valid for their intended data types and stay valid throughout the application that is driving this data.