Case Study: Sympower achieves scalable energy forecasting and real-time grid optimization with Databricks

Sympower leverages Databricks to help stabilize Europe’s energy grid

Sympower, a European energy flexibility company, helps stabilize the electricity grid by balancing supply and demand for commercial and industrial customers. As renewable energy and electrification increased grid volatility, Sympower needed more precise forecasting, stronger data governance, and better analytics to support data-backed bids and real-time decision-making. To address this, the company turned to Databricks and its Data Intelligence Platform.

With Databricks, Sympower improved data management, streamlined forecasting workflows, and made insights more accessible across the business. The platform enabled advanced forecasting models, better governance and lineage, AI-driven analytics, collaborative tools, and serverless dashboards, allowing Sympower to prototype and deploy new models faster and more collaboratively. The result was more robust forecasting and a stronger ability to manage roughly 2 gigawatts of flexible capacity across Europe.

Sympower

Rik van der Vlist

Senior Machine Learning Engineer