Building a Real-time Analytics and Data Warehousing Solution for Large-Scale Payment gateway

About project:

Client overview

The client, a fintech company, needed a scalable data warehousing solution to handle increasing volumes of payment data efficiently. Their existing infrastructure struggled with data growth, impacting accurate payment tracking and financial reporting, which prompted the need for a more robust solution.

Tech Stack:

PostgreSQL, PySpark, Airflow, Tableau, Python, Payment APIs.

Time to deliver project:

8 weeks

Problem

  • The client needed a robust data warehousing solution to store and process large volumes of payment data. Their current system struggled to scale with growing data, affecting payment tracking and financial reporting accuracy.

Inspection

  • We analyzed the existing payment processing systems, assessed the data flow and bottlenecks, and evaluated the volume of transactions to design an efficient ETL pipeline and a scalable data warehouse solution.

Resolution

We built a PostgreSQL-based data warehouse, designed a PySpark-based ETL process for handling large payment datasets, and integrated the data with Tableau for visual analytics. The project improved report generation speed by 40%, completed in 8 weeks.

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