completed
DATA
2024

Enterprise Data Engineering Pipeline

ETL pipelines and database optimization for large-scale data processing at Refonte Learning.

Python
Apache Airflow
PostgreSQL
Docker
AWS
Tableau

🎯 The Problem

Refonte Learning needed efficient data processing capabilities to handle large-scale educational data from multiple sources. The existing manual processes were time-consuming, error-prone, and couldn't scale with the growing data volume. There was also a need for real-time analytics and machine learning model integration.

💡 The Solution

Developed comprehensive ETL pipelines using Python and Apache Airflow for automated data processing. Implemented database optimization strategies for PostgreSQL to improve query performance. Created cloud-based data warehouses on AWS and built interactive dashboards using Tableau. Integrated machine learning models into real-time analytics systems for predictive insights.

🚀 The Outcome

Successfully improved data processing efficiency by 70% and reduced manual intervention by 90%. The automated pipelines now handle terabytes of educational data daily, providing real-time insights to stakeholders. The system supports data-driven decision making and has enabled the development of personalized learning recommendations for students.

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