Throughout the race, Red Bull can gather a number of inputs from the vehicle in terms of telemetry, audio, video and other input to help optimise it, as well as their tactics.
"We believe we're leaders in this kind of activity, says Cadieux.
"But even though we're very capable today, there's still huge potential to do better," he adds.
But what made IBM's offerings stand out in a crowded data management market?
"If you go back seven or eight years ago, computationall fluid dynamics (CFD) was our first venture into high performance computing, [but with] IT using other types of infrastructure. What's really changed is we've taken some of the early lessons from HPC and we've now applied tthat to many more use cases that are [now] mainstream in the company."
In other words, Spectrum Scale has a wider reach than previous - or some current - technology, saving time and - perhaps most importantly - money.
"We're using IBM Spectrum Scale and that file system to manage CFD, but also to manage metrics and simulation across aerodynamics and vehicle dynamics across the business," says Cadieux.
"So we used to have things that ran on individual machines and then scaled up, and what we've been able to do is take those increasingly demanding use cases and put them all through the Spectrum Scale environment, which gave us much more capacity, much more performance and allowed us to high levels of storage management, to take data from expensive disc and demote it to more affordable disc," he says.
"We've been able to consolidate actiivties in the company into a shared resource controlled by IBM software-defined infrastructure with Spectrum Scale."
Cadieux describes an enablement to work in "an agile way" with Spectrum Scale.
"We found a bottleneck - constraining what engineering [did]. We've been able to scale up the Spectrum Scale envorment and stay ahead of the curve, and be very responsibe to the business as it continues to evolve in improved simulations of analytics."
Finding peace in data: an interview with Alice Genevois, senior data science manager at Lloyds Banking Group
Genevois wanted to be a marketer - then she discovered data science
'If history has taught me anything, it’s that open ultimately becomes the winner,' says Hillary Ashton
SageMaker Clarify can discover potential bias during data preparation and after training, says AWS
'The overarching goal is to connect all the devices so we can have an overview from birth to trash'