Data Automation

A key challenge was capturing data from a dynamic frontend where forms and data structures frequently changed. The backend needed a way to ingest this data without requiring constant code updates, ensuring a seamless flow to a MongoDB database.

We engineered an intelligent data pipeline that fully automates the flow from the frontend to MongoDB. The core of the solution is a dynamic schema mapping system that intelligently interprets incoming data structures and maps them to the correct database collections and fields. Key features included:

• A flexible API endpoint capable of accepting varied data payloads.
• A schema inference engine that analyzes incoming data to determine its structure.
• Dynamic mapping logic that routes data to the appropriate MongoDB collections.
• Automated creation of new fields within documents as new data points are introduced from the frontend.

This automation eliminated the need for manual backend adjustments when frontend forms were updated, drastically reducing development overhead and deployment times. The system provides a robust, scalable, and future-proof solution for data ingestion, allowing for rapid iteration on the frontend without backend dependencies.