Project Overview
Airline Metrics (Upgraded) is an AI‑enabled, cloud‑based analytics platform rebuilt to support the technical and operational demands of airline revenue management and distribution analytics. The project focused on redeveloping a legacy system into a modern web application that consolidates data from GDS, NDC, direct web bookings, BSP, ARC, PSS, and accounting systems into a unified and consistent data model.
As Lead Developer from January to March 2026, I designed and implemented a scalable architecture using Laravel, React, MySQL, Redis, Docker, and TailwindCSS, with AI‑driven analytics integrated through Python and Ollama. The platform delivers high‑performance dashboards and advanced reporting for revenue, network performance, booking class analysis, origin‑destination flows, and contract evaluation, enabling near real‑time insights and consistent metrics across commercial and revenue teams.
Key Technical Challenges Addressed:
Normalizing large volumes of heterogeneous airline data from multiple distribution and accounting systems
Ensuring consistent and accurate revenue calculations across ticketed, forward, and flown datasets
Optimizing complex analytical queries to support fast, interactive dashboards
Designing a scalable architecture that supports growing data volume and concurrent users
Integrating AI‑driven analytics and decision support without impacting system stability or response times