Empowering Progress - Building a Personalized Training Goal Ecosystem with Databricks

Learn how Tonal, the home strength training system company, developed a comprehensive Training Goal ecosystem to help members better track their fitness progress using Databricks tools. Discover the four-part solution that addresses user feedback about difficulty measuring fitness journey progress, including new preference options for capturing fitness aspirations, weekly metrics that accumulate as members complete workouts, personalized weekly targets for guiding progress, and enhanced workout details showing how each session contributes to individual goals. Explore the technical implementation leveraging Spark for computing Training Goal metrics, MLflow for managing model development, and Workflows for orchestrating data pipelines within the Databricks ecosystem. Understand how these tools enabled the successful launch of the Training Goal system on schedule while supporting scalability, reliability, and providing a more meaningful, personalized approach for members to track their fitness progress. Gain insights from Giuseppe Barbalinardo, Senior Director of Data Science and AI at Tonal, and Kristi Korsberg, Senior Manager of Data Science and AI at Tonal, as they share their experience building this data-driven solution that transforms how users engage with their fitness goals.