Network Rail owns and operates the entire rail infrastructure in the UK; their challenge is to keep all the trains running on time and to maximize the services provided by the rail providers that run on its infrastructure. Network Rail needed to predict the results of train delay incidents and how to best deal with them to make sure the service runs smoothly. With the UK rail network being the busiest and oldest in the world, this is no easy task and relies on the power of big data and data science! Anya Rumyantseva Data Scientist Pentaho, a Hitachi Group Company Michael Fish Sales Engineer Pentaho, a Hitachi Group Company Caio Moreno Professional Services Senior Consultant Pentaho, a Hitachi Group Company

1. Predicting the Result of Incidents
with Big Data and Data Science
Michael Fish, Pentaho Sales Engineer, Hitachi Vantara
Caio Moreno, Pentaho Consultant, Hitachi Vantara
Anya Rumyantseva, Pentaho Data Scientist, Hitachi Vantara

3. Agenda
Solving Network Rail challenges using Pentaho and Data Science techniques
• Network Rail overview
• Challenges
• Implemented approach
• Demo
• Future vision

4. Who Is the Prospect?
Network Rail is the owner and infrastructure manager of the rail network in
England, Scotland and Wales.
• Manage the Infrastructure that all trains run on
• Their job to get as many services running on the network as possible
• If services are late or don’t run and it’s Network Rails fault; they are heavily fined
What's the challenge made up from?
• 20 thousand miles or track
• 40 thousand bridges and tunnels
• More than 25 hundred stations
• Bridges, Level Crossings, embankments etc.
• Freight Services
• Financial performance metric is -£200m below target*!
* According to the latest Quarterly report (Q3 2016/2017)

5. Increasing demand on Britain's railway
Oldest rail network in the world
Busiest rail network in the world

6. Increasing demand on Britain's railwayTrain delays are frustrating…

7. Increasing demand on Britain's railway
…and expensive

8. FINES
Service ProvidersTrain Providers
NWR’s Mission:
• Minimize Disruption
• Maximise Utilization
• Reduce Fines
• Increase Profits
First Step:
Delay
Attribution
How Are Delays Handled?
• Who’s fault was
the delay?
• What was the
cost of the delay?
• Who has to pay
for the delay?
Network Rail

9. Our Approach
• Develop connectors to Network Rail data feeds in Pentaho
• Build Pentaho dashboards for delays monitoring
• Apply machine learning algorithms to the train delays data
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10. Our Approach
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Complex Use CaseCross-functional Team

11. How It Worked
Pentaho Platform
Engineer solution to
collect Data, blend,
prepare and
visualize results
Data Science
Analyse historic delays
to model delay
attribution
Services
To connect to NWR data
Service – Custom Plugin
Results!

12. Demo Agenda
• Connecting to Network Rail Live Data Feeds
• Analytics on Live Train Movement Data
• Pentaho Dashboards for Rail Network Condition Monitoring
• Predicting Incident Attribution: Machine Learning Orchestration in Pentaho

13. Demonstration

14. Summary
What we covered today:
• The Challenges faced by the rail network
• This isn’t just a BI problem, it’s a data engineering and data science problem
• Successfully realized high value in predicting the attribution of delays