Inmarsat

Inmarsat, a world-leading British satellite telecommunications company, provides telephone and data services to users worldwide using portable or mobile terminals, which communicate with ground stations through satellites.

Historically, Inmarsat has been reliant on manually-entered and maintained data for the aircraft using its products and services. When aircraft are transferred, sold or re-registered, these changes aren’t always captured, resulting in a database of customer information that becomes outdated over time. Inmarsat recognised the value of using extensive internal data to improve insights and its product offering. However, this was only possible once the unique ID of their onboard hardware could be matched against the correct aircraft.

Once matched, Inmarsat can enrich its dataset to help them extract powerful insights and improve product offerings.

“We received positive feedback from Inmarsat’s Maritime team about Datatonic, which had worked with them on a similar project to match vessel names and IDs. We were keen to see if this success could be repeated for the Aviation business unit.

The Datatonic team worked seamlessly with Inmarsat’s own internal teams, particularly IT and data engineering. They adapted to Inmarsat’s complex security and system requirements, demonstrating Datatonic’s knowledge as subject matter experts, and delivered an outcome that surpassed expectations.” – Jeremy Jackson, Lead Insight Partner, Inmarsat

Over the course of 10 weeks, Datatonic designed and built a scalable data processing pipeline on Google Cloud Platform. The platform has allowed Inmarsat to match its unique hardware IDs to commercially registered aircraft with high accuracy through satellite geolocation data on a daily basis.

The project was split into two phases: first, a data science proof-of-concept to assess the feasibility and design the matching algorithm, followed by a production phase, to orchestrate and automate the end-to-end solution.

As part of the solution, our team of data scientists and data engineers built the following:

An SQL pipeline in BigQuery to clean, process and match the internal and external data sources. This enabled going from raw datasets to final tables that can be used by business users and in reporting.

A matching algorithm suited for aircraft particularities, which consisted in identifying aircraft and unique hardware IDs that were co-located at a given minute. Custom confidence metrics were designed to assess the quality of all candidate matches, filter out inaccurate matches, and report on match performance.

Tableau dashboards were built on top of reporting tables to analyse and monitor matching performance over time.

The end-to-end data processing pipeline was executed in BigQuery and orchestrated with Google’s new Workflows tool to be executed on a daily basis, upon receiving new data. Continuous monitoring, alerting and testing was also incorporated into the solution for robustness.

Cloud Workflows was chosen instead of Cloud Composer as the orchestrator for two reasons: 1) Workflows is a fully serverless technology, making it easy to deploy and includes all necessary monitoring options, 2) The Workflows billing model is usage-based (per step executed), making it the right choice for a solution that requires processing upon receiving new data.

Matching terminal data to commercially registered aircraft with high accuracy through satellite geolocation data, on a daily basis has enabled Inmarsat to enrich its dataset and extract powerful business insights and improve product offerings.

“The data output from this project has been integrated into all of our key reports and dashboards. It has facilitated a number of planned projects and could enable future projects that haven’t yet been conceived.” – Jeremy Jackson, Lead Insight Partner, Inmarsat