How to Build an Amazon Pipeline with Bright Data + Mage AI
Blog post from Bright Data
The text details the creation of a data pipeline that collects and analyzes Amazon product data using Bright Data's Web Scraping API and Mage AI, culminating in a PostgreSQL database and a Streamlit dashboard for visualization. This pipeline facilitates product discovery and sentiment analysis of reviews via Google Gemini AI, with the entire process managed through Docker, requiring minimal local setup. The integration benefits from Bright Data's ability to handle proxies, CAPTCHAs, and parsing, while Mage AI manages the scheduling, retries, and branching of data flows. The setup allows users to gather product intelligence without building complex scraping infrastructure, and the pipeline is scalable for monitoring various e-commerce platforms by adjusting parameters and dataset IDs. Additionally, the text provides guidance on troubleshooting common issues, scaling the pipeline for larger datasets, and customizing it for different data sources.