Aviation Data Architecture & Pipeline Engineering

Why is aviation data so hard to unify?

Aviation runs on parallel identifier systems and incompatible formats. The same airport is LHR to a booking engine and EGLL to an operations system; the same flight can carry a marketing number, an operating number, and a callsign. Schedules arrive as SSIM files, positions as ADS-B messages, operational notices as terse ICAO-format NOTAM text, and inventory through GDS platforms such as Amadeus and Sabre.

Most organisations accumulate one integration per feed, each with its own mapping logic. Over time those mappings drift, reports disagree, and every new product starts with weeks of data cleaning. The architectural problem is not volume — it is the absence of one canonical model that every feed resolves into.

What does an AeroCraft data architecture include?

Every engagement starts with a canonical entity model: airports, carriers, aircraft, routes, flights, and events, each resolved to both IATA and ICAO codes with history preserved. Ingestion services then map each source into that model at the edge, so downstream systems never see raw formats.

• Streaming ingestion for live feeds (ADS-B, flight status) and scheduled ingestion for timetables and reference data
• Identifier resolution across IATA, ICAO, callsigns, and codeshares, with an audit trail for every mapping
• A storage layer split by access pattern — hot operational state, time-series history, and analytical warehouse
• Data contracts and validation at every boundary, so a malformed upstream file fails loudly instead of corrupting reports
• Documented, versioned APIs over the model, so new products consume data rather than re-integrate it

How do you modernise legacy systems without a big-bang migration?

We use a strangler pattern. The new pipeline runs alongside existing systems, reading the same inputs and producing comparable outputs. Once outputs reconcile, consumers move over one at a time, and the legacy component is retired only when nothing depends on it. There is no cut-over weekend and no period where reporting goes dark.

This matters in aviation because operational systems cannot pause. An airline's operations control or an airport's resource planning has to keep working throughout, so the migration plan is designed around their schedule, not ours.

What proof is there that this architecture works at scale?

AeroCraft runs this architecture in its own products. Skyinfo, our global flight intelligence platform, unifies live tracking, schedules, and delay prediction for 7,883 airports across 233 countries and more than 500 airlines, with data refreshed around the clock. The same normalised model sits behind our 16-endpoint aviation API suite.

That means the patterns we propose are not theoretical. They have handled real feed outages, identifier changes, and schedule reissues in production.

What changes for the business once the data is unified?

Reports stop disagreeing, because every team reads from the same model. New products start from an API instead of a data-cleaning project. Analysts spend their time on questions rather than reconciliation, and operational teams can trust what a dashboard says at three in the morning.