TransGlobal Logistics

Case Study

TransGlobal Logistics

TransGlobal Logistics, a multinational provider with a 3,500-vehicle fleet across 28 countries, faced escalating processing costs and delays with their legacy data warehouse. This hindered real-time analytics for route optimization and predictive maintenance, slowing decision-making and inflating operational expenses.

Turnover

12 months

Company

TransGlobal Logistics

Industry

Transportation

Budget

$450.000

Reducing processing time and price by 90% with Databricks

TransGlobal partnered with Dateonic, a Databricks consultancy, to replace their costly data warehouse with a Spark cluster on Databricks. Dateonic designed a migration plan, using Auto Loader to ingest operational data into Delta Lake and Delta Live Tables to streamline analytics-ready datasets. They integrated MLflow to deploy AI models for logistics optimization, combining vehicle telemetry, GPS, and weather data.

Cut fuel costs by 9.3% with AI-driven route optimization
Reduced delivery estimation errors by 68%
Lowered processing costs by 45% while scaling analytics

Driving Results

With Dateonic’s guidance, Databricks turned data into a strategic asset for TransGlobal. Fleet managers gain real-time insights, maintenance predictions minimize breakdowns, and customer service offers precise delivery updates. The shift delivered a 280% ROI in the first year, cementing TransGlobal’s edge in logistics.

TransGlobal Logistics