The automotive industry is on the cusp of a data explosion. As vehicles become increasingly intelligent, the need for technology solutions that support large-scale, real-time data migration, privacy, and analytics becomes more urgent.

EMR notes connected car sales overtook nonconnected cars for the first time in 2022, with the market expected to grow at a CAGR (compound annual growth rate) of nearly 17%. Juniper Research projects that the number of connected vehicles in service will reach 367 million globally by 2027.

So, how can this naturally distributed data be used in the aggregate effectively, and how does data enhance the automotive value chain?

Every second, connected cars can generate or use large amounts of data for driver assistance, information access, entertainment, and software updates. Data must also be immediately flagged for road safety alerts such as flooding or road closures if needed. When in product development, data are used to analyze driver behavior, refine safety features, and develop new services.

For fast-moving data to function properly, a fully automated migration solution that can move large dynamic datasets is required. Automotive businesses using a hybrid cloud/on-premises infrastructure will also need real-time replication to maintain data in hybrid environments and transfer them between necessary locations.

According to Cox Automotive, electric vehicles, plug-in hybrids, and hybrids combined are expected to account for almost 24% of the market, with electric vehicles alone accounting for over 10% of total sales. More models, incentives, and discounts informed by analytics will help spur sales, but it won’t be easy. This is where CX (customer experience) becomes the raison d’être for investing in technology and applications within the automotive industry.

Companies need data-driven customer intelligence to gain market share with competitive consumer offerings. The key to success is the ability to securely and in real-time support the sharing of internet access and data with devices inside and outside the vehicle. From there, automotive businesses need to leverage AI (artificial intelligence) and analytics to continue providing innovative, secure services.

Using smart vehicle data requires a solid technical foundation, enabling automotive businesses to leverage data to introduce new high-value services, one of which is AI. Once organizations have received the data, they must organize the information to use it properly. In light of this, automotive industry executives are advocating for a standardized data-sharing framework built into supply-chain components.

While attractive to industry leaders, consumers may have a different perspective. These new rules require them to consent to data use and raise privacy concerns. This will heavily influence the use of AI in smart-vehicle analytics. While beneficial, AI is under increasing scrutiny for potential compliance issues and is subject to growing governmental regulation.

OEMs (original equipment manufacturers) and their suppliers face a double-edged sword with unstructured connected car data. They need real-time environmental data for customer safety and deeper analysis of customer behavior for new services. However, growing consumer and regulatory demands for data privacy are challenging, especially with the increased amount of consumer data, partly due to AI.

To comply with privacy regulations, modern migration and management must be prioritized. Legacy methods of moving large datasets into data lakes, coupled with the addition of Gen AI, pose privacy risks due to disorganization.

To combat this, companies must organize data into manageable chunks, housing it in various locations such as the cloud or on-premises and categorizing it according to specific divisions or projects. Adapting an advanced migration solution will securely support data migration at scale, ensuring each location works with current data and allowing for seamless transitions between cloud platforms and data centers.

Outside migrations, OEMs must stay current on industry regulations and implement security measures to protect privacy data including data anonymization, encryption, VPNs (virtual private networks), and authentication. As connected cars evolve into mobile workspaces, their data privacy must match the best device defenses.

Vehicle consumers expect their connected cars to be as useful and personalized as with other connected solutions such as phones and laptops. To capture the market, leaders must successfully examine petabytes of data for customer intelligence that sparks exciting, innovative services and security measures. We foresee more use of cloud-agnostic solutions, which can easily move between cloud and on-premises environments, giving OEMs the flexibility to stay ahead of the fast-moving, continuous data flow.

With billions in potential service revenue at stake, OEMs and their partners need a data migration solution that provides the organization and scale needed to analyze enormous sums of unstructured data. Those able to effectively manage the migration, use, and security of the data will quickly elevate themselves above the competition.

 

Paul Scott-Murphy, CTO at Cirata, wrote this article for Futurride. His company enables data customers to continuously move petabyte-scale data to the cloud of their choice, fast, and with no business disruption.