backend
professional
Content Recommendation System
Scalable recommendation engine using BigQuery and Django serving 2M+ users daily with personalized content.
Year
2022
Duration
2 year(s)
C
backend
Overview
Designed and built a sophisticated content recommendation system that analyzes user behavior and preferences to deliver personalized content to over 2 million users daily. The system uses BigQuery for large-scale data processing and Django for the recommendation API.
The Challenge
Processing and analyzing massive amounts of user interaction data to generate real-time personalized content recommendations at scale.
The Solution
Built a data pipeline using BigQuery for analytics and a Django API for serving recommendations. Implemented caching strategies and optimized queries to handle 2M+ daily users with low latency.
Key Features
Real-time personalized recommendations
BigQuery data processing
Scalable API serving 2M+ daily users
Behavior analysis and tracking
Redis caching for performance
Technologies Used
Python
Django
BigQuery
PostgreSQL
Redis
REST APIs