Masthead Data x Formula E
Catching Data Anomalies in Real Time During Live Races
Saved monthly for single data engineer
30+
hours
Data stack
Google BigQuery, Python, dbt, Looker
Site
Industry
Electric motorsport
Company size
200 - 500 employees
Founded
2011
Masthead transformed our data operations overnight. With a seamless deployment, we gained real-time visibility into telemetry and pipeline health. During races, we can immediately detect when data is delayed, duplicated, or missing — and respond on the spot. Previously, we spent hours after races diagnosing issues and explaining gaps. Now we resolve problems in real time, which has been a game-changer for reliability and performance.
Will Allen
Senior Data & AI Manager
Formula E is the world’s premier all-electric racing championship — where cutting-edge engineering meets high-stakes competition. Every lap generates a torrent of real-time telemetry from the car, and that data powers everything from race strategy to live broadcast graphics and fan engagement.
For Formula E, data isn’t something you analyze after the race — it’s part of the race. Teams, engineers, and broadcasters depend on reliable real-time signals to make decisions in seconds and deliver on-screen moments like fastest lap, energy strategy, and performance trends as they happen.
With Google Cloud as a key technology partner, Formula E runs a modern data platform built for speed and scale — turning millions of events into trusted, real-time insights for teams and fans worldwide.
The Challenge
Formula E operates one of the most demanding real-time data environments in sports. Around 90% of the data they process is telemetry, and it is not only used internally by teams — it is also surfaced live on television during race broadcasts.
During a race lasting roughly one hour, Formula E receives millions of telemetry events. Any delay, duplication, or pipeline failure can directly impact live dashboards, broadcasting metrics, and downstream consumers. For the data team, it is critical to detect issues immediately — not after the race ends.
Formula E runs hundreds of streaming pipelines writing into BigQuery during races. The team recognized that traditional data monitoring approaches would not scale:
Manual checks were impossible given the volume and speed of updates ( 100+ tables are updated during the race)
A SQL-first data monitoring approach introduced too much lag between a check and a real issue occurring is not good enough.
Running SQL checks every minute across hundreds of tables raised concerns about both cost and whether it would deliver the required detection speed.
The team needed a solution that could detect anomalies across the data warehouse in real time, at race scale, without adding operational overhead or inflating costs.
The Solution
Formula E adopted Masthead to provide real-time anomaly detection and pipeline observability for their BigQuery environment.
During a one-hour race, Formula E streams over 2 million events using Kafka and Pub/Sub. Masthead monitors BigQuery ingestion behavior using BigQuery audit logs, allowing the team to identify anomalies and outliers in real time — without integrating into streaming systems and without accessing customer data.
Masthead’s log-based, event-driven architecture enabled fast deployment and immediate coverage:
No access to customer data: Masthead does not read or ingest Formula E’s telemetry data.
No SQL execution: Masthead does not run SQL queries against customer tables.
Automatic anomaly detection: ML-based thresholds are learned for pipelines and tables, with alerts triggered when patterns fall outside acceptable ranges.
Real-time alerting: issues such as delays, duplication, or abnormal ingestion patterns are surfaced as they occur.
Formula E gained a system that can monitor hundreds of real-time updated tables and ingestion pipelines, ensuring no events are lost, and pipelines perform as expected under intense race conditions.
Masthead’s UI and UX were also critical at this scale: the team needed monitoring that stays usable during high-velocity ingestion and makes it easy to spot problems immediately. This reliability supported the creation of dependable data products used for downstream experiences such as car simulators and live broadcast metrics.
Formula E car simulators rely on telemetry collected from real race cars to power realistic experiences. Masthead ensures this data is captured reliably and alerts the data team to issues in real time.
The Results
Full coverage of ingestion pipelines and tables within one hour of deployment, enabling immediate observability with minimal operational effort.
Real-time visibility into table performance and pipeline behavior, helping the team detect and resolve issues during races rather than after.
Reduced operational and recovery costs, avoiding expensive remediation efforts and eliminating the need to re-engage third-party vendors to recollect missing race data.
Faster delivery of fan-facing data products, because Formula E could trust the quality and reliability of real-time data powering broadcasts and new experiences.
