Voyeurchat - What is validating data

The unique constraint ensures that no two rows have the same values in their columns.

The not null constraint is placed on a column and states that data is required in that column.

However, the inserts and updates allowed by referential integrity occur when the data inserted is located in the lookup table.

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Let's take the time and list those parts here and explain why they should be considered.

These are the 3 major areas where you'd want to be sure that proper data validation is applied properly.

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.

What this means is data validation, in order to be as successful as it can be, must be implemented at all parts that get the data, processes it and saves or prints the results.

The main types of constraints in SQL are check, unique, not null, and primary constraints.

Check constraints are used to make certain that a statement about the data is true for all rows in a table.Referential integrity is a key aspect in data integrity that is usually associated with two tables; the lookup table and the data table.Typically, referential integrity is applied when data is inserted, deleted, or updated.Is it, by any chance, to enter numbers when an application is expecting numbers out of you, the user?If so, then you're already well under way to grasping the full understand of just what data validation is all about.Consequently, the inserts and deletes allowed by referential integrity come from data located in the lookup table.

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