Data transformation
Modifying data as it flows through an automation reformatting dates, concatenating strings, converting currencies, parsing JSON. Every production workflow transforms data at least once.
Expert insight
Transformation logic is where most workflow bugs hide, not in the trigger or the API call, but in the step that reformats a date, splits a name, or converts a currency string to a number. These steps deserve the same testing rigor as the "real" actions around them, with real edge-case inputs (empty strings, unexpected formats), not just the one sample record used to build the workflow.
In a real workflow
Phone numbers from a form are converted to E.164 format before being sent to the SMS provider.
Common mistakes
- Transforming data in several places, so the same field ends up formatted differently.
- Losing the original value, which makes debugging hard.
Complexity level
Requires some familiarity with automation concepts.
Related terms
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