Making data actionable for Germany’s long distance rail network
The Challenge
How to process complex data to support rapid but informed decisions affecting millions of customers
The Result
A suite of visual data-informed tools to manage Germany’s rail network and its hundreds of thousands of daily passengers
Our Expertise
- AI & Machine Learning
- Full-Stack Development
- UX & UI Design
The Brief
We created several powerful tools and highly optimized data visualizations for Deutsche Bahn , which are used in production every day to make critical decisions.
Based on machine learning algorithms, Peak Spotting uses load,- and capacity prediction data of Deutsche Bahn’s entire network. The software makes millions of data points instantly available to yield and traffic managers. Besides optimizing the present traffic situation, the tool predicts 100 days into the future to coordinate trains, optimize price management and provide better service to passengers.
In Numbers
Travelers per year
Travelers per day
Rail network to manage
Our Approach
To make data truly actionable, Peak Spotting integrates highly customized visualizations with task management and collaboration tools.
When I first saw the visualizations, it almost had me in tears. I was finally seeing what was happening.
Team Member of Deutsche Bahn AG
The full application from the timeline macro view on the left to the detailed train-level information on the right (obfuscated data).
To make data truly actionable, Peak Spotting integrates highly customized visualizations with task management and collaboration tools.
Application Screencast
Credits
In collaboration with
- Moritz Stefaner
- Christian Laesser
- Christian Au, Deutsche Bahn
- Kevin Wang, Deutsche Bahn