The rise of the connected car is turning Big Data into a big business opportunity – provided companies can harness, store and access that data. On this front, Quantum is pioneering innovative approaches that promise pivotal development cost savings for players across the automotive spectrum. The company has earned a reputation in the field of data protection and has recently begun to use data more predictively.
Asking questions of the data
“We’ve been in the automotive sector for over a decade, dealing with IT and corporate data. In the last six or seven years, we’ve continued to grow more in the research and design portion of the sector,” explained Molly Rector, Vice President of Marketing at Quantum. Extrapolation is the key. As she elaborated: “You can ask questions of the data. You can predictively use that data to cut the number of simulations and the number of physical prototypes, reducing time and cost.”
Pointing to crash test simulation as an example, Rector noted that where a company would previously have run perhaps ten simulations, now it can run hundreds of thousands with simulated data. “We really are opening up a new world of capabilities, not just in terms of time to market, but also by generating really good results to make better decisions.”
One priority will be to continue efforts to make the systems easy enough to use so that a scientist, and not just an IT specialist, can use them relatively easily – Molly Rector, Quantum
Quantum has worked with a range of traditional vehicle manufacturers around the world, from Asia, across Europe and the US. It has also collaborated with racing teams from Formula 1 and NASCAR. More recently, the rise of the connected car has opened up new challenges and partnerships. “With the evolving market of autonomous driving, new players are jumping up in very unexpected countries,” Rector told Megatrends. “They could never go out and compete in the traditional automotive market, but they are doing autonomous work in smaller markets.”
Opportunities abound. With the rise of connectivity and greater autonomy, Quantum has been considering how to collect sensor data and transfer it safely to where it needs to be. As Rector explained: “There’s the question of how to collect the sensor data coming off an autonomous vehicle. We have been working with the military, for instance, where there is a need to be able to collect data in a war zone. We have rugged equipment that can go into the trunk of a vehicle to collect that sensor-generated data. It’s then crucial to be able to recover that data from such vehicles.”
The right fit
Once the data has been acquired, the challenge turns to transferring it to the researchers and designers and storing it. At this point, the right data storage programme could make or break a project. “The systems that can cost-effectively store this kind of data for a business unit are very different from those you would use for Microsoft Exchange or Oracle, for example. One of the biggest obstacles for these researchers and developers is to figure out the right kind of systems they need,” she commented.
With a rapid increase in connectivity, Quantum saw a leap in the capacity requirements among its automotive customers in a short period of time. “We looked into the R&D processes of the vehicle manufacturers and component suppliers to see how they were generating this data. What we saw was that they are attaching more and more technology – sensors, new cameras with better resolution, LiDAR, sonar – to collect more and more data as they drive their R&D efforts,” explained Andrew Mortemore, Quantum’s Sales Director for Autonomous/ADAS Data Solutions.
That technlogy generates high volumes of data very quickly, creating large, complex files. “These files do not take advantage of compression technologies, so it’s essential to find a way to transfer that data quickly in order to be able to access it or share it. Importantly, you also need a way to economically store it. That’s where we come in,” added Mortemore.
Vehicle manufacturers and component suppliers are attaching more and more technology – sensors, new cameras with better resolution, LiDAR, sonar – to collect more and more data as they drive their R&D efforts – Andrew Mortemore, Quantum
In this sense, Quantum’s experience with the media and entertainment industry serves as a valuable precedent. “95% of the data generated by these automotive customers and companies involved in advanced driver assistance systems (ADAS) consists of media files or like-video files. We see them adopting the same types of workflows as media and entertainment companies because the traditional IT strategies of storage just aren’t feasible,” Mortemore explained.
Competitive environment
Much of the rise in demand for Quantum’s expertise stems from the competitive nature of the industry, where the race to be first to market with a new technology has assumed greater importance. “The automotive companies have always been concerned about safety and what happens as they design a more efficient engine. What they need to accomplish has not changed. What has changed is the competitive landscape and how quickly innovation is occurring. Just think about Tesla and other similar companies coming into the market. The pace at which the market is evolving has changed considerably,” said Rector. “The ability to use high performance computing systems and data analytics to remain competitive or to get ahead of the competition has become extremely strategic.”
Not long ago, companies would have been looking at a time to market window of five years. Now, suggested Rector, they are looking at a two-year time-span. “What we can do is share our experience in similar use cases from other industries. We partner with these users to significantly change their business models. Simulating a crash test instead of physically doing it, and knowing you can trust the data, represents a huge business model change.”
Quantum itself faces competition as new players enter, but believes it has something unique to offer. “The market is not very crowded today. There are many IT companies out there that sometimes get the nod from a business unit to do the work. Then they discover their systems either are too expensive or they are not designed for this use case and they end up not working,” she explained. “There is only a handful of organisations that have systems purpose-built for this type of heavy data analytics and global data sharing.”
That said, it’s a lucrative field with strong growth potential, and new entrants could arrive. “I think people will try to get into the field. You can’t pick up a magazine without reading something about the importance of data-driven businesses,” added Rector.
“There are some big companies looking at new ways to solve the problem. We are a step ahead of the competition because we’ve been following these kinds of problems for quite some time.”
Still work to do
Quantum faces a number of headwinds, but will be putting considerable effort into ease of use in particular. “One priority will be to continue efforts to make the systems easy enough to use so that a scientist, and not just an IT specialist, can use them relatively easily,” said Rector. “We are working towards the idea of an analytics system in every researcher’s work group area that is easy enough to manage and configure so that you don’t have to be a specialist to use it.”
Achieving this will add scale – and scale is crucial. As previously noted, thanks to growing demand for, and supply of, connected car technology, a burgeoning volume of data will need to be handled. Covering nearly all Tier 1 suppliers in North America and 85 Fortune 100 organisations, Quantum’s automotive customer base is wide. Big Data really is big business.
This article appeared in the Q1 2017 issue of Automotive Megatrends Magazine. Follow this link to download the full issue.
