Advanced ETL Processor Data Validator guarantees to your application database that every data value is correct and accurate.

• Data type validation
• Range checking
• Code checking
• Complex validation
• Pattern checking

One of the simplest forms of data validation is verifying the data type. Data type validation answers such simple questions as "Is the string alphabetic?" and "Is the number valid?"

As an extension of simple type validation, range checking ensures that the provided value is within allowable minimums and maximums. For example, a character data type service code may only allow the alphabetic letters A through Z. All other characters would not be valid. As with data type validation, your application's interface can typically provide the necessary range validation, although as a design alternative you could create a business rule to handle range validations.

Code checking is a bit more complicated, typically requiring a lookup table. For example, maybe your application calculates sales tax for only certain state codes. You would need to create a validation table to hold the authorized, taxable state codes. This validation table could be part of a business rule, or it could be implemented directly in the database for query lookup.

Pattern checking when you checking structure of the data field for example social security number format or car registration number. Regular expressions used quite often for pattern checks.

It does not matter which business you are in sooner or later you will discover that there is something wrong with the data ant it has to be validated. Here when Advanced ETL Processor Validation can help.

Note:
 Records can also be rejected by the Server.

To change Validator properties double click on it


Debugging Validation

To start debugging validation press Process Data button. To test data edit it in the Data grid.



To Change Validation Rule properties double click on it

To add new Validation rule drag and drop it from Validation rules panel



There more than 190 Validation Functions at the moment. They are grouped in five different categories

1. String
2. Number
3. Date
4. Time
5. Regular Expressions

To choose appropriate category click on Category toolbar


It is also possible to apply several validation rules to Input field by joining them



Data is considered as validated when all validation rules are succeeded.