Data and AI

Finding Altitude In Architecture

Data and AI

Finding Altitude In Architecture

The Client

We helped a leading global airline modernize more than 700 data pipelines with a metadata-driven architecture that enhanced restartability, reusability, and real-time visibility across its enterprise data ecosystem.

The Customer’s Challenge

Every flight depends on precision. Behind the engines and airspace lies another network that must stay perfectly aligned: data. For a global airline with more than 16,000 employees and a fleet of 96 aircraft, that network had become fragmented. Cargo, operations, and scheduling teams ran data pipelines in isolation. Failures during restarts caused cascading delays. Code could not be reused. Monitoring was scattered across dashboards, each showing only a fragment of the whole picture. The airline needed a metadata-driven foundation that could unify its data landscape, improve restartability, cut compute costs, and provide complete visibility into performance and governance.

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