Dance: Data-driven E-Bike Maintenance

Industry: Sustainability & Green Tech
Solution: Data Analytics for Predictive Maintenance
Impact: Operational insights for improving fleet reliability and battery performance

Overview
Dance is a Berlin-based e-bike subscription service on a mission to make cities more liveable through sustainable transportation. With a growing fleet and massive volumes of ride data, they turned to Ishango to help make sense of it all—and unlock smarter maintenance planning.

The Challenge
Dance needed to analyse sensor and usage data to understand battery health, charging habits, and ride patterns across its e-bike fleet. The goal was to move toward predictive maintenance and reduce downtime—improving both service quality and sustainability.

The Ishango Approach
Ishango’s team tackled noisy and inconsistent sensor data, cleaned and structured it, and conducted in-depth descriptive analysis. From battery degradation to ride distances and charge cycles, the team uncovered key insights and built clear visualisations for decision-makers.

The Result
Dance gained a clearer understanding of how their fleet performs under real-world conditions and where predictive interventions could prevent issues before they occur.