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Palantir x Scuderia Ferrari

Telemetry data diagram animation

Partners in Ultimate

Palantir powers Scuderia Ferrari’s data
analysis, turning performance data into
race-time decisions.

Partnership Overview

Illustration of Ferrari F1 car in motion with fuel consumption chart

"In using Palantir, we have basically taken all of the complexity that lies around managing such a vast amount of data out of our hands. And we really focus our time on extracting value from the analyses that we run, focusing on the product that we develop."

Marco Adurno
Head of Vehicle Performance
Scuderia Ferrari

01 —

The Partnership

Palantir and Scuderia Ferrari believe in speed – ruthlessly prioritising the hardest problems, using data to find the best solution.

Formula 1 teams have extremely limited time to test their car on the track, in the wind tunnel, or with computer simulations, so it often comes down to race weekends: combining immense amounts of data with engineering expertise, at speed. That’s where Palantir comes in.

Palantir allows Scuderia Ferrari to ingest millions of data points, removing the time-consuming data cleaning and integration step and providing a structured, relatable framework – the Ontology – for making consequential decisions.

Palantir’s analytical tools allow Scuderia Ferrari engineers to leverage this ontology, a digital twin of their data, to create analyses, rapidly iterate on them, and adjust various axioms or modelling decisions. From part reliability – understanding a part’s lifecycle so it doesn’t fail during a race, to determining which configuration will perform best on a given track, Palantir’s technology draws the link between man, machine, and data.

Foundry dashboard mockup showing Ferrari F1 car in wind tunnel simulation

02 —

The Tech

Palantir integrates several types of Scuderia Ferrari’s data, such as sensor data (from races, tests, simulations or testing equipment), parts information, or data from experiments and tests; but the key source is data from car sensors in the form of high frequency time series.

Time series is a special kind of data due to its complexity and scale – thousands of sensors reading up to a thousand times per second. The complexity is due to its structure: each of those data points is part of a stream of sensor data, not an isolated observation, and engineers need extremely quick access to only the most important data to keep costs under control.

Palantir Foundry contextualises time series data within a data model – what we call the Ontology. This framework reveals the relationships between different pieces of data, and organises them into human-readable “objects” (like cars, or parts), rather than tables, for example, where a row won’t necessarily have a physical equivalent. Using this ontology, organisations can interact with and analyse the data with code, low-code, or no-code tools; and optimise transformations that speed up calculations.

03 —

Why it Matters

Time series data is everywhere: in transportation, in energy production, and in healthcare.

While most organisations aren’t constrained by sporting regulations, most all of them are constrained by time and costs. And every company wants their work to run as efficiently as possible, just like Scuderia Ferrari.

At all of these organisations, decision makers value low latency in making the data available in the platform; fast calculation on data; and a variety of tools for different types of users. At Scuderia Ferrari, some engineers require the flexibility of code-based tools, while others require low-code/no-code interfaces for making decisions. Palantir provides powerful tools for diverse user bases.

Moreover, time series are not just limited to sensor data. In 2020 the world was captivated by a time series that saw new data points daily: the number of people testing positive for Covid-19. The forecasts and projections from analysing this data became critical for saving lives.

Making decisions on the sales desk, in the manufacturing plant, in the lab, and in the paddock, engineers worldwide use Palantir Foundry to analyse their time series data whenever time matters most.

Aerial view of a race track