Case Study: Hitachi achieves safer, more reliable railways with Databricks

Hitachi - Customer Case Study

Hitachi, a global rail solutions provider, faced the challenge of monitoring overhead lines and infrastructure issues manually, which made railway maintenance slow, reactive, and costly. To improve safety and reliability, Hitachi used Databricks Lakehouse to build AI-driven digital solutions that could analyze large volumes of train video data and identify potential problems in near real time.

Databricks implemented a platform using Delta Lake for storage and pipelines, MLflow for model management and deployment, and Databricks SQL for monitoring dashboards. As a result, Hitachi shifted from reactive to predictive maintenance, helping rail network owners spot issues faster, reduce costly disruptions, save significant maintenance costs, and speed up time to market for ML models while improving data team efficiency.

Hitachi

Andreas Herman

Lead Data & AI Architect