Software with RapidMiner Data Analytics @ Lufthansa Agenda 1 - - PowerPoint PPT Presentation
Software with RapidMiner Data Analytics @ Lufthansa Agenda 1 - - PowerPoint PPT Presentation
From Prototype to Operative Software with RapidMiner Data Analytics @ Lufthansa Agenda 1 Lufthansa Industry Solutions: Who We Are 2 Our Daily Challenges 3 FlightPrediction @ Lufthansa 4 Lufthansa Industry Solutions & RapidMiner 2
Agenda
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Lufthansa Industry Solutions & RapidMiner
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FlightPrediction @ Lufthansa
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Our Daily Challenges
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Lufthansa Industry Solutions: Who We Are
IT Consulting and Systems Integration
Lufthansa Industry Solutions combines the dynamics of an SME with the economically secure background of Lufthansa; an internationally acting global corporation.
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Lufthansa Industry Solutions
We are
Services overview
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Lufthansa Industry Solutions
IT Consulting and System Integration Strategy and Management Consulting IT Service Provider
Strategy Consulting IT System Operations IT System Integration & Development IT Consulting
(processes, technologies, infrastructure)
Operations of full business processes BPO specialized provider Organization & Process Consulting
Process Consulting / Process Organization Organi- sational structure Infra- structure Application
- Mgmt. &
Operations
Norderstedt
Hamburg
Cologne
Berlin
Wetzlar
Frankfurt
Basel
Miami Wolfsburg Oldenburg
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Locations
Our
Norderstedt
Hamburg
Cologne
Berlin
Wetzlar
Frankfurt
Basel
Miami Wolfsburg Oldenburg
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Locations
Our
Hard Facts
100% owned by
Lufthansa
208 Mil. €
total revenue (46% of which within the Lufthansa Group)
>200
customers
>1300
trained employees
Managing Director
Bernd Appel
Founding
1998 as Industry Solutions division within Lufthansa Systems AG
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AirPlus LGBS Lufthansa Passenger Swiss Austrian Lufthansa Industry Solutions Lufthansa Systems
Finance and Service Companies Passenger Airlines Digital Service Companies
Lufthansa Industry Solutions
Lufthansa Technik LSG Sky Chefs
Aviation Industry
Lufthansa Cargo
Air Freight
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Projects Successfully Delivered
Many
About Me
Fabian Werner Born 1985 Ph.D. Mathematics (Number theory)
Past Present Future
- Predictive analytics:
- Classification,
regression, recommender systems, probabilistic modelling, …
- RapidMiner, R, Python,
PHP, Teradata, Oracle, Hadoop, …
- Probabilistic modelling
- Time series analysis
- Bayesian learning
- Learning theory
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Quick Facts
Our Daily Challenges
Lufthansa Internal
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Dashboarding Predictive Analytics (Deep) Machine Learning Data Ingestion
- Airplane punctuality
- Competitor information
- Airfreight load monitor
- Arrival times
- Passenger connection
- Fuel & Weight forecast
- Predictive maintenance
- Recommend fligths
- Document and image
recognition
- Damage recognition
via audio data
- Bots (see Mildred)
- Live flight data
- Weather data streams
- Airplane sensor data
Process Model
Scoping Phase
Laboratory stage Implementation stage
Laboratory stage Implementation stage
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FlightPrediction @ Lufthansa
We predict the arrival time
- n aircraft takeoff
The Cycle
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Goal & Process
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Landing Takeoff Departure Arrival
Rolling Rolling Airtime Gate - to - Gate
Prediction Point Prediction Time
Goal & Process
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Landing Departure
Rolling Rolling Airtime Gate - to - Gate
Arrival Prediction Point Takeoff Prediction Time
Goal & Process
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Landing Departure
Rolling Rolling Airtime Gate - to - Gate
Arrival Prediction Point Takeoff Prediction Time
Accuracy of existing prediction
- Avg. deviation estimated vs. actual OnBlock
Goal & Process
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Landing Departure
Rolling Rolling Airtime Gate - to - Gate
Arrival Prediction Point
Accuracy of existing prediction
- Avg. deviation estimated vs. actual OnBlock
Takeoff Prediction Time
How? Unleashing The Power of Big Data
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Predicted Arrival Time Historized Flight Data Stream Eurocontrol Weather Data Stream Data Warehouse Reporting Server Real-Time Data Historic Data
The Cycle
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Parameters for the Model
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Flight Duration Passenger data
- #Passengers with connection
- % occupied seats
Route, distance, … Weather
(en route & @destination)
Season Lagged features Runway(s) Weight Traffic situation Delay @ Takeoff
Parameters for the Model
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Flight Duration Passenger data
- #Passengers with connection
- % occupied seats
Season Lagged features Runway(s) Weight Delay @ Takeoff Special disruptions Actual data needed Route, distance, … Weather
(en route & @destination)
Traffic situation Capacity index & airport information still missing
The Cycle
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- A few rolling window features are good!
- Prefer models that can be trained fast:
Play around with features instead of models.
Model Building
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The Cycle
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Visualization: Performance Monitor
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Data Made Up (No Actual Data)!
10 20 30 40 50 60 70 80 90 100 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Error @ flight done %
- ther prediction
- ur prediction
10 20 30 40 50 60 100 90 80 70 60 50 40 30 20 10
Error @ minutes before arrival
- ther prediction
- ur prediction
Error Error
How To Save Money?
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Gate Z50 Gate Z99
How To Save Money?
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Gate Z50 Gate Z99 Gate A1
How To Save Money?
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Gate Z50 Gate Z99 Gate A1
Visualization: Benefits Monitor
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Data Made Up (No Actual Data)!
1 2 3 4 5 1 2 3 4 5 6 7
Potential benefit (k€)
Saved Passengers Potential Benefit
Potential Benefit 1000*€ #Saved Passengers
The Cycle
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- Runs every hour
- Asserts that …
- enough data
- enough predictions
- predictions produced fast
- not too much missing data
- …
Automation: Supervisor
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Supervision of Model
- Supervisor & dashboard as early as
possible
- Business needs to understand the
real impact
- Translate Data Science to business
language
- Need for standards
- Prototype needs to be translated to
real application
- You do not want to rebuild everything
Lessons Learned
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Go To The Real World Fast – Make Everybody Understand The Benefits
- Partnership founded in 2015
- RM widely used in Lufthansa
- Keeps up with market technologies
- For prototyping and productive applications
- Still lacks some software engineering capabilities …
- We pair it up with Hadoop, Oracle, Teradata, R, Python, …
- Lufthansa Industry Solutions: certified RapidMiner trainers
Partnership
Lufthansa Industry Solutions | RapidMiner
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