1. 6 October 2016 Irmingard Eder Data Scientist, Munich Re
Center for International Earth Science Information Network - CIESIN - Columbia University Gridded Population of the World, Version 4 (GPWv4): Population Count. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC).
Big Data Munich Re VIII. International Istanbul Insurance Conference
6 October 2016
Irmingard Eder
Data Scientist, Munich Re

2. 1 2 Agenda Data Analytics Framework
Example for Current Analytics Activity
19. November 2018

3. Big Data in Trend Radar Big Data Digitization Internet of Things
Augmented and virtual worlds
Big Data
3D Printing
Computing Everywhere
Loc-based services
Telematics
Smart Home
Industrialization 4.0
Digitalization
Wearable Devices
Predictive Analytics
Robotics/Drones
Open Data
Internet of Things
Collaborative Consumption
Big Data
Digitization
Citizen Development
Mobile Health Services
Virtual
Assistant
Systems
Crowdsourcing
User Centered Design
On-Demand-Everything
Context-aware Computing
Digital
Identity
Integrated Systems
Cybersecurity
Risk-based
Security
Autonomous Systems and Devices
Internet of Things
Web 4.0
Web-Scale IT
Automated Decision Taking
Software-defined Anything
Haptic Technologies
Cloud/Client Architecture
New Payment Models
19. November 2018

4. When does it become BIG Data?
40,000,000,000,000,000,000,000
Zettabyte
Exabyte
Petabyte
Terabyte
Gigabyte
Megabyte
Kilobyte
Byte
Yes or No
43 zettabytes of data will probably be generated by 2020
300 times the volume in 2005
4 KB Commodore VC 20
3.5 inch floppy disk
Data contained in a library floor
4 TB in Memory Big Data Platform MR
Petabyte Storage Big Data Platform
All words ever spoken by humans
Google, Facebook, Microsoft…
Source: IBM
19. November 2018

5. Big Data Analytics is a Combination of Methods, Technology, Data and People
Regression Models
Machine Learning Models
Text Mining
Technology
Hardware (Compute power)
Software (SAS, R, Spark, …)
Data
Internal Data
External Data
Structured Data
Unstructured Data
People
Data Scientists
Data Engineers
Business People
19. November 2018

6. 1 2 Agenda Data Analytics Framework
Example for Current Analytics Activity 2
19. November 2018

7. Pilot Fact Sheet M.IN.D. – Digital Big Data Platform for efficient Risk Management
Results
Benefits
M.IN.D
Easier, faster and cheaper information about exposure and losses
Transparency on all exposures and losses independent of participation and risk assessment
Database on loss events allows in-depth trend detection
Faster & more effective claims management
M.I.N.D. = Manager for INteractive Disaster Assessment
19. November 2018

8. Contact: Irmingard Eder, Data Scientist, Munich Re ieder@munichre.com
Image: Bayerische Zugspitzbahn Bergbahn AG / Lechner
Center for International Earth Science Information Network - CIESIN - Columbia University Gridded Population of the World, Version 4 (GPWv4): Population Count. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC).
Thank you!
Contact:
Irmingard Eder,
Data Scientist, Munich Re
© 2016 Münchener Rückversicherungs-Gesellschaft © 2016 Munich Reinsurance Company