Advanced ETL Processor uses the Transformer to change data format, structure, or values between the Reader and Writer. Use it for field mapping, splitting values, cleaning names, applying functions, and checking transformed rows before the job writes anything permanent.
What You Will Learn
- Open and configure the Transformer object.
- Map input fields to output fields.
- Use transformation functions for strings, numbers, dates, lookups, JSON, XML, and regular expressions.
- Preview transformed records before sending them to the Writer.
Before You Start
Use sample data with known problem values. A Transformer is easier to trust when you can see exactly what it did to the awkward rows.
Transformer Docs
The Transformer documentation explains how the object modifies data format, structure, and values inside a transformation.
Review the Transformer Toolbar for mapping tools, record navigation, source-data preview, and process controls. If the grid is empty, check the previous step execution log before blaming the Transformer. It may be innocent, which is rare but possible.
The examples show common work such as splitting a date into day, month, and year, or making store names readable. The Auto Mapping section covers faster field mapping when the source and target names line up.
For expressions, start with Transformation Functions, then use the dedicated references for strings, numbers, dates, lookups, JSON, 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.