Case Study: Viessmann achieves scalable, data-driven energy efficiency with Databricks

Building an energy-efficient world

Viessmann, a global provider of sustainable climate and renewable energy solutions, was facing major data scalability and efficiency challenges as its connected devices generated more than 2.5TB of machine data per day. Legacy systems were costly to manage and too inefficient to support its growing IoT, monitoring, and service needs, making it harder to deliver energy-efficient customer experiences.

Using the Databricks Data Intelligence Platform, Viessmann built a central lakehouse for data and analytics, enabling faster ML development, predictive maintenance, remote service sessions, and better insights into energy use and system health. The results included anomaly detection for issues like water-pressure drops, forecasting of energy consumption and component lifetime, and broader data democratization through Power BI dashboards, helping Viessmann improve product reliability, customer support, and sustainability.

Viessmann

Marina Pausch

Head of Data Science