The Formula 1 Grand Prix is again in Singapore for the only night race in the F1 circuit.
I had the opportunity to take a peek at how SAP’s HANA in-memory computing system helps McLaren to harness the Big Data streaming in from their cars’ onboard sensors to fine-tune – in real time – the team’s race strategy.
SAP HANA provides McLaren with a dashboard for comprehensive awareness and real time decision making during a Formula 1 race or practice.
In this digital age of high performance computing, pertinent telemetry data is constantly being captured and transmitted by on-board sensors on the car for modelling and analysis by the team management back in the control room – be it during test practices, qualification runs, or the actual race itself.
Each of McLaren’s two cars is fitted with 120 sensors, capturing data that includes tyre and engine temperatures, tyre and fluid pressures, gear changes, brake wear, speed and acceleration – all critical information that have a bearing on the performance of the car and therefore the outcome of the race.
The sheer bulk and velocity of these data are simply too overwhelming for traditional data logging or database management and analysis software to handle – especially in real time.
That is why – with the astronomical growth of data generation and consumption – IT vendors are investing huge resources developing tools to deal with Big Data, while enterprises are also embracing these tools to harness Big Data for greater business effectiveness and profitability through applications such as predictive analytics.
One such toolkit is SAP HANA – an advanced computing solution that makes use of in-memory database technology to tame the 3 V’s of Big Data: Volume, Velocity and Variety.
McLaren has been in partnership with SAP since 2008 and has recently implemented SAP HANA to “own” the real time Big Data pouring in from their cars’ on-board sensors.
SAP HANA enables the management team to be constantly aware of the status of the car and race standing, and make use of real time predictive analytics to make split second decisions to fine-tune the race strategy to win the race.
Such decisions include deciding the optimal windows of opportunity to make pit stops during the race, depending on the location of the cars on the circuit and based on real time telemetry data streaming in from McLaren’s race cars.
Chat with Kurt J. Bilafer on Big Data and data analytics
Kurt tells me that it used to take two days just to model the data, now it happens in sub-seconds.
Kurt J. Bilafer, Regional Vice President, Analytics, SAP Asia Pacific Japan.
This is invaluable given the neck-breaking pace of an actual race and the short two-week cycle between races.
During test practices, the drivers can be debriefed immediately on where they had overbraked or under-accelerated, while the memory was still fresh on their minds.
We had a most interesting chat on how Big Data and data analytics were ready for extensive applications in a whole spectrum of industries.
Another application in the Sports arena was for the NBA.com website, which makes accessible to fans the extensive archive of historical data as well as real time statistics from ongoing NBA games – to nurture greater fan engagement and loyalty.
Tags: analytics, Big Data, cars, dashboard, F1, Formula 1, HANA, McLaren, predictive, racing, SAP, Singapore, telemetry