Data Mapping in Make: Parse AppHighway JSON Correctly
Complete guide to Make.com's data mapping for AppHighway tools. Iterator, Aggregator, Array Functions, nested JSON parsing, and complex data transformations.
TL;DR
- Use Iterator to process arrays from API responses
- Aggregator combines multiple items back into single output
- Array Functions: map, filter, reduce for data transformation
- Parse nested JSON with dot notation: data.user.email
- Text Parser extracts specific fields from unstructured responses
- Router splits data flows based on conditions
Why Data Mapping Matters
Make.com requires explicit data mapping between modules. AppHighway tools return structured JSON - understanding how to parse, transform, and map this data is essential for building robust scenarios.
Using Iterator for Arrays
Iterator processes each item in an array individually
Example: Structify returns array of contacts → Iterator → Process each contact
Use Case: When API returns multiple results that need individual processing
Using Aggregator to Combine Results
Aggregator merges multiple items back into single bundle
Example: Iterator processes 10 items → Aggregator → Single array output
Use Case: Combine processed results before sending to database or API
Next Steps
Master Make.com data handling
Download Make Blueprints
Get 10 scenarios with advanced data mapping examples.
Make.com Integration Guide
Learn the fundamentals of connecting AppHighway to Make.com.
Map Data Like a Pro
Mastering data mapping in Make.com unlocks the full potential of AppHighway tools. With Iterator, Aggregator, and Array Functions, you can build sophisticated data transformations without code.
Ready to map complex data? Download our blueprints with real-world mapping examples.