Cubic3 Processes 10x the Data for No Extra Cost — While Connecting 25 Million Vehicles

High-value mobile assets like luxury cars are meant to offer a sense of freedom. However, the connectivity these vehicles rely on is often subject to heavy restrictions such as regional regulations, roaming limits and other barriers that can make it more expensive — or outright impossible — to connect to navigation and entertainment services. Cubic³ aims to bring true freedom to mobile assets by managing and coordinating mobile, satellite and ISP connectivity for 25 million vehicles in over 200 countries. 

With its connectivity platform, Cubic³ creates a bridge between vehicle manufacturers and mobile carriers, internet providers and satellite internet services. However, delivering consistent, connected experiences worldwide generates and demands huge volumes of data.

“We were seeing massive growth in the data we were managing, the sources it was coming from and the customers generating it,” says Richard Springer, Director of Data and Business Intelligence at Cubic³. “And we were finding that our data pipelines and processes were becoming more complex and costly to maintain.” 

To get the scalability and low-risk data pipelines it needed to handle its growing data volumes, Cubic³ turned to Snowflake’s AI Data Cloud running on Azure. With Snowflake, Cubic³ has doubled its customer base while maintaining cost controls and high performance — and finding a platform for continued innovation simultaneously.

Previously, Cubic³ used an on-premises data lake and warehouse to store and process key customer data workloads. However, when its legacy platform vendor announced end-of-life for its data solutions, Cubic³ had no choice but to look for a new approach.

Springer was keen to find a data platform provider that could support Cubic³ with the scalability and performance it needed — as well as headroom to expand and innovate with new data products and use cases.

“All our customer data was stored in our data lake, so we had to make a smart move,” explains Springer. “I felt confident in Snowflake, because its platform was built in the cloud, for the cloud.”

In 2021, Cubic³ migrated to Snowflake’s AI Data Cloud to get a future-ready data platform and low latency that could power extensive analytics use cases. Vehicle, customer and telecommunications data lands in Microsoft Azure Blob Storage and Azure Virtual Machines. Thanks to easy integrations with Snowflake, that data is then directly ingested by the AI Data Cloud or injected into data pipelines through Kafka Connectors. Finally, teams can use Looker to visualize data or send it to dashboards.

Initially, Cubic³ primarily used Snowflake on Azure to power essential analytics for the company and its customers. All manufacturers that work with Cubic3 get dashboards to help them identify anomalies, understand user behavior and consumption, and successfully localize SIM cards. This is essential to delivering the connected vehicles experiences that help Cubic³ — and its customers – stay ahead of the competition. 

For instance, car manufacturers may need these tools to identify and automatically remedy situations where customers are overpaying for roaming fees. Or, these dashboards may help manufacturers automatically localize SIM cards to comply with eCall regulations or other rules imposed on vehicles around the world.

These crucial features were just the beginning of a long journey of data innovation. Cubic³ has since started using dynamic tables to reduce latency across data workloads and dashboards.  Streamlit apps also help the company simplify how teams access the datasets they need. And for its most data-hungry customers, Cubic³ has used Snowflake’s collaboration features to establish direct data shares — accelerating transfer while maintaining security and data privacy.

Much like the vehicles it connects and manages, Cubic³ is going places. 

Since it began using Snowflake, the company has doubled its customer base and now manages over 25 million vehicles — and thanks to Snowflake, Cubic³ shows no signs of slowing down. “With Snowflake, we know we can deploy new instances anywhere in the world in just half a day and establish a data share in three hours,” says Springer. “That’s been such a big help in forging customer relationships and getting new deals through.”

Despite expanding its customer base and data volumes, Cubic³ continues to see lower costs than ever. Today, the company spends roughly the same amount on data management and processing as it did in 2019, while processing around ten times more data. For broader analytics costs, Springer estimates Snowflake has delivered a 50% reduction in overall spend.

Snowflake also delivers more performance for existing workloads. One example is metering and billing, a previously manual process that took around a week to complete. With Streamlit apps running in Snowflake, it now takes just one hour — saving valuable time that can be reinvested elsewhere in the business.

For Springer and his team, there’s a wide open road ahead of them thanks to Snowflake. The team is already experimenting with expanding its data and applying new AI and machine learning algorithms to extract more insights and create more value for customers.

The company is also looking at how it can apply Cortex AI and large language models so people can query data in natural language, lowering the barrier to entry for non-technical teams.

“What else can I say about Snowflake? It’s been really good to us,” says Springer. “I enjoy the platform, the teams are great and it’s allowed us to do some truly amazing things for our customers and the vehicles they produce.”