At StampedeCon 2012 in St. Louis, Bill Eldredge of Nokia presents: At Nokia, we expect to save millions on avoided license fees this year on a single “Big Data” project by creating a symbiotic relationship between our traditional RDBMS storage and our newer Hadoop cluster. Our hybrid approach to data enables us to manage the convergence of structured and unstructured data, and save money. In our case we use Hadoop to process and import data into traditional systems. We have found that this use of Hadoop as a preprocessing engine has enabled maximum value to be derived from our systems, our data and our people.

1. Making Your
Analytics
Click to edit Master title style
Investment
Pay Off
Bill Eldredge
Sr. Manager, Nokia Data Asset
August 1, 2012
StampedeCon
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2. Overview
• Nokia and Our Big Data Challenge
• Making Hadoop Pay
• Cost Avoidance
• Product Innovation
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3. Nokia’s History: 1865 to Now
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4. The Four Cardinal W’s
Location and Time Add Human Context to Social and Search
WHAT
WHO
WHERE
WHEN
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5. Great Mobile Products That
Sense the World
CREATE A LEADING “WHERE” PLATFORM
WIN IN SMART CONNECT THE INVEST IN FUTURE
DEVICES NEXT BILLION DISRUPTIONS
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6. Taking Our World Class Map Making
Capabilities to the Next Level …
2.4 1500+
400+
Validations
Million Map
Changes Attributes
per Day 11B+ 181
Probe per
Local
Month
Field Offices
245
Field Cars 196
Driving the
Roads Countries Automatic
37k+ km Feature
Roads Recognition
9 out of 10 in-car nav systems use Nokia’s Location
6
Platform

7. One Platform, Enabling
Contextually Rich Mobile Experiences
Content
Platform Maps Positions Places Directions Guidance Traffic
Smart Data
Apps
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8. Data, Data, Data
+1B Search Queries
Annually 11B Probe Points
Processed Monthly
147M 24M
Map Tiles Route Requests
Served Daily per Month
+19M Geocoder
Requests Daily 55M Positioning
Requests Daily
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9. Data Silos
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10. Central Big Data Analytics Platform?
" One cluster for all needs?
" Do it ourselves, or with help?
" If we build it, will they come?
" Will it pay off?
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11. Phased Approach
Oozie
Map Reduce Pig Hive
Quartz
HBase
Scribe HDFS
HBase
FTP
HBase
2010 2011 2012
Build Enhance, Make It Robust…
Get Data, and Make It Pay
Use it Ourselves
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12. • Nokia and Our Big Data Challenge
• Making Hadoop Pay
• Cost Avoidance
• Product Innovation
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13. Best of Both Worlds
• Key device datasets • Key location datasets
• Dedicated reporting team • Reporting largely self-serve
• Expensive storage (€20k/TB) • Inexpensive storage (€2k/
TB)
Key Integration Principle
Aggregated Event-level
Data Data
Projected Savings 2012:
€6 Million
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Nokia Internal Use Only

14. Integrated Solution
Touch-points/Devices
Consumer-Facing/
Online Serving Front-End
(“Fast World”)
Enterprise-Facing/
Back-End
(“Slow-World”)
Oracle/MySQL Reporting
Activity Hadoop Cluster
Hadoop Tools
Logging Cluster (Cognos, Tableau)
Teradata
Advanced
Analysis
Other RDBMS
Tools
Streaming
Data Bulk Data Sources
Sources
Analytics Platform Other systems
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Nokia Internal Use Only

15. Integrated Solution – Applied to Music
On-device
app usage Touch-points/Devices
Consumer-Facing/
Online Serving Front-End
(“Fast World”)
Enterprise-Facing/
Back-End
Improved Music (“Slow-World”)
Recommendations
Oracle/MySQL Reporting
Activity Hadoop Cluster
Hadoop Tools
Logging Cluster (Cognos, Tableau)
Teradata
Advanced
Analysis
Other RDBMS
Tools
Streaming
Download CDN Bulk Data Music
Data
logs & Logs Sources metadata
Sources
Collections
Projected Benefit:
Analytics Platform Other systems
3M Euros +
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Nokia Internal Use Only

16. Overview
• Nokia and Our Big Data Challenge
• Making Hadoop Pay
• Cost Avoidance
• Product Innovation
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17. The Map Is Changing…
Cities are
possibly our 60%
greatest World’s Population in
Cities in 2030
achievement,
constantly RICH
HUNDREDS
OF MILLIONS MILLIONS
evolving as we Network of
Sensors
of Mobile
Devices
of Mobile
Users
discover new
technologies
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Nokia Internal Use Only

18. …and Needs to Become Personal…
Synthesis How
A of Us as Who When
Individuals
Living Interactions
Map Where with the
Real World
What
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Nokia Internal Use Only

19. …to Everyone
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Nokia Internal Use Only

20. Using Different Types of Data…
Asserted Observed Reference Derived
Data Data Data Data
…to Create a Human Motion Graph
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Nokia Internal Use Only