E-commerce Data Pipeline with Airflow, Google Cloud, Twilio, and MySQL

In today’s digital landscape, businesses gather massive amounts of data. This project showcases a scalable and reliable data pipeline for an e-commerce platform, using Apache Airflow for workflow orchestration, Google Cloud Storage for data management, MySQL for database storage, and Twilio for real-time error notifications.

Project Overview

The system ingests, processes, and stores hourly batch data from a hypothetical e-commerce platform, with real-time monitoring for errors or data discrepancies.

Key Technologies:

1. Apache Airflow: Automates data ingestion and processing workflows.
2. Google Cloud Storage (GCS): Primary storage for raw and processed data.
3. MySQL: Stores cleaned, validated data for querying and analysis.
4. Twilio: Sends real-time SMS alerts for pipeline issues.

Pipeline Workflow:

1. Data Simulation: Simulates and ingests e-commerce data into Google Cloud Storage every hour.
2. Data Processing: Apache Airflow processes and cleans the data, storing it in both GCS and MySQL.
3. Error Monitoring: Triggers immediate SMS notifications via Twilio for any processing errors.
4. Scalability: Cloud-based infrastructure scales with data growth, maintaining performance with large datasets.

Validation:

Checks the number of records processed and stored in MySQL to ensure pipeline accuracy and consistency between source data and processed records.

This project demonstrates how modern cloud tools and automation frameworks can efficiently manage, process, and derive insights from data. Check out the code and full setup on my GitHub repository.