Title
J.B. Hunt speeds up freight matching with a Databricks lakehouse on Google Cloud
the ability to deliver freight recommendations to carriers 99.8% faster than before.
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Description
J.B. Hunt built a unified BI and AI lakehouse platform for its J.B. Hunt 360 digital freight marketplace on Google Cloud using Databricks, Delta Lake and MLflow, paired with Immuta for automated data governance, to process real-time location pings and IoT telemetry from trucks and containers. The platform trains thousands of ML models in under four hours, delivers freight recommendations to carriers 99.8% faster than before, and has produced $2.7 million in IT infrastructure savings.
the ability to train thousands of ML models in less than four hours and the ability to deliver freight recommendations to carriers 99.8% faster than before.
Company
J.B. Hunt
…mission of creating the most efficient transportation network in North America, J.B. Hunt Transport, Inc. offers asset- and non-asset- based transportation solutions, including dynamic freight matching. This involves connecting a business’s specific shipping needs with available ca…
Region
North America
…e industry — streamlining logistics, optimizing experiences and reducing costs. In its mission to create the most efficient transportation network in North America, J.B. Hunt ran into significant roadblocks caused by legacy architecture, rapid growth in data, and limited AI capabilitie…
Industry
Transportation
…s to boosting productivity, resulting in significant IT infrastructure savings. I N D U S T RY Transportation S O LU T I O N • Freight logistics • Recommendation engine T E C H N I C A L U…
Problem
J.B. Hunt's carrier world is deeply fragmented, with an estimated 3.5 million drivers across the industry, and its legacy enterprise data warehouse platforms locked up data, limiting its usability for real-time decision making. Data refreshes had only ever been available overnight at best, but trucks move constantly, and systems struggled to process and store massive data generated from location pings every 15 minutes across hundreds of thousands of loads, making telemetry-based ML and AI use cases nearly impossible.
…ing into consideration details such as price, weight and location. The problem? The carrier world is deeply fragmented, with an estimated 3.5 million drivers across the industry. Improving upon a matching system that considers that much fragmentation require…
Solution
J.B. Hunt worked with Google Cloud and Databricks Lakehouse to build an open, interoperable data platform for J.B. Hunt 360, using Delta Lake as an open storage layer to put all data in one place and stream real-time web, mobile, location and IoT data for faster analytics and ML, and MLflow to make code and experiments reproducible across data scientists. Immuta was layered on for automated data governance, including columnar-level data masking and global/local security policies, enabling secure self-service data analytics, data science and reporting across business analysts and engineers.
With Delta Lake, J.B. Hunt not only has the ability to put all of its data in one place for easy access across the organization
Business value
J.B. Hunt can now train thousands of ML models in less than four hours and deliver freight recommendations to carriers 99.8% faster than before, while realizing $2.7 million in IT infrastructure savings and productivity gains. Databricks has also enabled new capabilities like virtual track and trace feeding a predicted-time-of-arrival model, and brought data teams together to accelerate data science productivity.
…bility to deliver freight recommendations to carriers 99.8% faster than before. J.B. Hunt has also experienced a significant impact on its business operations, realizing $2.7M in infrastructure savings and productivity gains. In the next year, the data team at J.B. Hunt will continue to scale its usage o…
AI capabilities
Predictive Analytics
…ble to securely fast- track improvements to its various applications, including a new platform capability called virtual track and trace, which feeds into a data science model called predicted time of arrivals. Databricks has also enabled the creation of web services that can then be serve…
Business functions
Supply Chain & Logistics
…p it create the most secure and efficient freight marketplace in the industry — streamlining logistics, optimizing experiences and reducing costs. In its mission to create the most efficient transportation network in North Ame…
Technology
Databricks Lakehouse Platform, Delta Lake, MLflow, Google Cloud, Immuta
…ICKS CUSTOMER STORY: J.B. HUNT Automating data governance across the enterprise Databricks is also being used in conjunction with Immuta, an automated data governance platform. “Databricks opens up many opportunities for self- service data analytics, data…
Headline outcome
…• Machine learning $2.7M in IT infrastructure savings increasing profitability 99.8% faster freight recommendations 4DATABRICKS CUSTOMER STORY: J.B. HUNT The impossibility of progress without uni…
Use case type
Predictive operations
…nd meaningful analytics. “What we’re doing from a data science point of view is building pricing models and load recommendation models to improve operations,” explained Douglas Mettenburg, Vice President of Engineering & Technology at J…
Capture details
- Captured
- 27 Sept 2026, 06:00 UTC
- Extractor
- unpdf@1
- Snapshot hash
- 1b621c545d5c6b61bfe362c00caa045f5b253d640e161dfb121f08238dc35051