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  1. Preface
  2. Introduction to Data Transformation
  3. Data Processor Transformation
  4. Wizard Input and Output Formats
  5. Relational Input and Output
  6. Using the IntelliScript Editor
  7. XMap
  8. Libraries
  9. Schema Object
  10. Command Line Interface
  11. Scripts
  12. Parsers
  13. Script Ports
  14. Document Processors
  15. Formats
  16. Data Holders
  17. Anchors
  18. Transformers
  19. Actions
  20. Serializers
  21. Mappers
  22. Locators, Keys, and Indexing
  23. Streamers
  24. Validators, Notifications, and Failure Handling
  25. Validation Rules
  26. Custom Script Components

Overview of Validators, Notifiers, and Failure Handling

Overview of Validators, Notifiers, and Failure Handling

When you design a transformation, you must consider the following questions:
  • What happens if the input data is invalid? For example, a date might have the wrong format, a string might be too long, or the records might be out of sequence.
  • What happens if data is missing from the input? For example, an address might omit the house number.
  • What happens if the input has an unusual structure? For example, the records might be out of sequence.
Any of these conditions might occur because of an input error. If so, they can cause transformations errors and failures.
The conditions might also occur under normal circumstances. For example, an input protocol might permit certain fields to be missing.
You can incorporate transformation features that detect such conditions and take appropriate actions. The following approaches are among the possible actions:
  • Fail the transformation and generate no output.
  • Fail a portion of the transformation, roll back its output, but permit the transformation to generate output for other portions of the data.
  • Continue the entire transformation, but write a message to a user log.
  • Continue the entire transformation, but write a message to the result file of the transformation.
This chapter explains what happens in the event of a transformation failure, and how you can handle failure conditions. It then explains how you can detect data validation errors that might cause failures, and how you can write notifications about such conditions to the output.


Updated March 03, 2021