Working with Validator

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

There are several types of data validation.

  • 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.

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 lookup object to hold the authorized, taxable state codes.

Pattern checking when you checking the 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 and it has to be validated. Here when Advanced ETL Processor Validation can help.


  • Records can also be rejected by the Server. *If you have several validation rules and one of them rejects the record and another discards it, the record will be discarded

To change Validator properties double click on it


  • If no data is present in the grid check the previous step execution log.

About input and output fields:

  • List of Output fields is always the same as Inputs.
  • List of Input fields is taken from the previous object

  1. Properties
  2. Create new tab
  3. Cut
  4. Copy
  5. Paste
  6. Delete
  7. Redo
  8. Undo
  9. Align Left
  10. Arrange Vertically
  11. Align Right
  12. Align Bottom
  13. Arrange Horizontally
  14. Align Top
  15. Space Horizontally
  16. Space Vertically
  17. Snap to grid/show grid
  18. Prints Mapping
  19. Print Preview Mapping
  20. Automap data
  21. Delete All objects
  22. Delete All Links
  23. Search Objects
  24. Process Data
  25. First Record
  26. Previous Record
  27. Next Record
  28. Last Record
  29. Show Objects Panel
  30. Zoom In
  31. Zoom Out
  32. Zoom back to 100%


We recommend giving the Validator name, it makes it easier to identify problems later.

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

To Change Validation Rule properties double click on it


Use <value> to include actual value into default value

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

There more than 190 Validation and 200+ transformation functions at the moment. They are grouped into five different categories

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

To choose the appropriate category click on the Category toolbar

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

Data is considered validated when all validation rules are succeeded.

If you have several validation rules and one of them rejects the record and another discards it, the record will be discarded

For more technologies supported by our ETL Software see Advanced ETL Processor Versions and Visual Importer ETL Versions

Confused? Ask question on our ETL Forum

  • aetl/processing_data/working_with_validator.txt
  • Last modified: 18/06/2015 12:08
  • by admin