Advanced ETL Processor uses the Validator to check incoming data against rules before the job writes it to the target. Use it for data type checks, ranges, formats, patterns, consistency checks, and controlled rejection of records that should not continue through the transformation.
What You Will Learn
- Add a Validator object to a transformation.
- Apply validation rules to input fields.
- Debug validation using sample rows in the data grid.
- Understand when records are rejected or discarded.
Before You Start
Use sample data with known bad values. If every test row is perfect, the Validator has nothing useful to complain about, and that is not how production data behaves.
Validator Docs
The Validator documentation explains how validation rules check data quality and stop invalid rows before they reach the Writer.
Start with What is Data Validation for the rule types: data type, range, format, pattern, consistency, and referential checks.
The Validator Screen section explains input and output fields. The Validator keeps the same output fields as the inputs, so this object is for checking records, not reshaping them.
Use Debugging Validation to process sample data, edit test values in the grid, and inspect validation rule properties. Give Validators clear names; future you will appreciate it when reading an execution log at 7:03 AM.
For rule details, use the Validation Rules index plus the dedicated references for strings, numbers, dates, times, and regular expressions.
Need Advanced ETL Processor First?
Download the Advanced ETL Processor trial before following the tutorial, or review Enterprise if you need scheduled unattended execution.