Case Study: Husqvarna AI Lab achieves predictive maintenance and personalized customer experiences with Databricks Lakehouse

Giving every gardener a green thumb

Husqvarna, a global manufacturer of outdoor power products with over a million connected IoT devices, struggled to turn fragmented device and operational data into actionable insight. Their existing AWS-native tooling and laptop-run Jupyter notebooks were costly, hard to maintain and didn’t scale, leaving teams siloed and forcing product decisions to be made on opinion rather than data.

By adopting the Databricks Lakehouse on AWS and centralizing data with Delta Lake, Husqvarna built scalable pipelines for map generation, personalization and predictive maintenance and democratized access for data teams. The result: clearer KPIs and real-time visibility into connected machines, earlier detection of maintenance issues, improved product development and customer service, and a shift from gut-driven to data-driven decision making.

Husqvarna AI Lab

Linus Wallin

Data Engineer