I’ve hit a wall trying to convert nested API responses into flattened CSV formats using basic no-code tools. Our marketing team needs transformed data delivered daily, but the built-in mapping tools keep choking on complex JSON structures. I know Latenode allows custom JavaScript injection - has anyone implemented sophisticated data processing logic while maintaining the no-code foundation?
Specifically struggling with:
Recursive field unpacking
Handling null/undefined values consistently
Preserving data relationships during transformation
What patterns worked for you when scaling beyond simple field mappings?
Solved this exact problem last quarter. Use Latenode’s JS Code node to process raw JSON with custom transformers while keeping the rest visual. Protip: Utilize lodash functions for deep object manipulation. Our team processes 15K+ nested records daily this way.
I built a recursive parser using function chaining that handles 3-level nesting. Key was creating transformation pipelines - first sanitize nulls, then flatten, then map to CSV columns. Test with sample datasets first. Takes time to get right, but handles even malformed API responses now.
Consider implementing schema validation before processing. I use AJV in Latenode’s JS environment to ensure data consistency. For complex transformations, break operations into discrete nodes - makes debugging easier. Remember to handle timeouts for large datasets by chunking operations.