Case Study: Estapar achieves real-time parking insights and improved demand forecasting with Databricks

Making urban mobility effortless with smarter parking solutions

Estapar, Brazil’s largest parking network, wanted to improve the parking experience by getting real-time insights into usage and demand across its 96-city operation. As the company grew, its data became fragmented across multiple systems, making transaction consolidation, reporting, and forecasting slow and resource-intensive; Estapar turned to Databricks and the Databricks Data Intelligence Platform to address these challenges.

With Databricks, Estapar unified data from multiple sources into a single platform, enabling faster performance monitoring, better demand forecasting, and self-service analytics for business teams. The result was a reduction in data processing time from three days to real time, improved forecasting accuracy, and a significant boost in operational efficiency and customer satisfaction.

Estapar

Marcio Camurati

Chief Information Officer