Case Study: Texas A&M Transportation Institute achieves safer traffic decisions with Databricks

Texas A&M Transportation Institute unlocks car sensor data on the Databricks Data Intelligence Platform

Texas A&M Transportation Institute (TTI) needed a modern way to analyze rapidly growing IoT and geospatial transportation data. Its legacy stack and scattered tools couldn’t scale to handle trillions of GPS points, making it difficult to collaborate, track data lineage, and produce the detailed safety insights clients and agencies needed. TTI turned to Databricks and the Databricks Data Intelligence Platform to centralize and accelerate its data processing.

With Databricks, TTI consolidated its workflows in the cloud and gained advanced analytics capabilities to work efficiently with terabytes of raw data. The improved platform helped TTI produce targeted studies, planning models, inventories, and surveys faster and at greater scale, supporting safer roadway decisions with better precision. Databricks enabled the institute to overcome its infrastructure bottlenecks and better operationalize massive transportation datasets.

Texas A&M Transportation Institute

Michael Martin

Associate Research Scientist