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AWS Customer Presentation - Razorfish

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  • Return on advertising spend (ROAS)
  • Transcript

    • 1. Edge in the cloud
      Salim Hemdani
      VP, Experiences and Platforms
      @shemdani
    • 2. 500,000,000,000
    • 3. 1,000
    • 4. 100
    • 5. 25
    • 6. 13
    • 7. What are these numbers?
    • 8. Numbers
      500,000,000,000 records
      1,000 clients
      100 markets
      25 data sources
      13 terabytes per day
    • 9. Agenda
    • 10. Time for a change
    • 11. Transition Service Agreement
      Move from Atlas
      • Traditional hosting environment
      • 12. Heavy on CAPEX
      • 13. Managed by Atlas/MSFT networking teams
      • 14. To be completed by October 2010; no interruption in SLA
      Move away from PVM
    • 15. Ad Serving Event Log
      Request
      hash(key) mod R
      FS01
      FS03
      FS02
      98101
      98104
      98115
      98201
      98203
      98004
      98007
      98065
    • 16. MapReduce (divide and concur)
      HDFS
      • Distributed data storage
      • 17. Distributed processing
      • 18. Language agnostic
      Any Language
      Job tracker
      Task tracker
    • 19. AWS
    • 20. Aggregate Ad Serving data
      Log Files
      File Export
      APIs
      Internet
      Client Provided Data
      Data Sources
      Presentation Layer
      Talend Data Flow Manager
      Direct Analytics Processing via EMR
      Web Application Layer
      ODBC
      Edge Provisioning DB
      OLAP
      Cache
      Cloud Storage S3
      HBase/SDB
      15
      Elastic MapReduce
    • 21. Name Brand Retailer Case Study
      Business challenge
      • Changing competitive landscape
      • 22. Decreasing web marketing effectiveness
      • 23. Monetization of their web assets
    • Bring it all together
      Product interest
      Affinity
      Generation
      +
      +
      In market Gamer
      Sport Enthusiast
      Purchaser Home Theater
      ( 1 of 36 “Personalization” segments )
    • 24. Drive a personalized message
      User recently purchased a home theater system and is now looking for sports games
      Target Ad
      ( 1.7 million per day )
    • 25. We import Atlas transaction level data
      24 servers
      S3 file storage
      Compress and upload 200 + GB of data per day
      ( 180 days = ½ Trillion ICA records )
    • 26. We use EMR to process and segment
      EMR
      S3
      100 Machinecluster created on demand
      ( 3.5 Billion records, 71 million unique cookies a day)
    • 27. Process and Cost
      This all happens in about 8 hours every day and is fully automated (previously 2+ days)
      And increased ROAS by 500% (to $74)
    • 28. Why AWS
      Efficient
      Elastic infrastructure from AWS allows capacity to be provisioned as needed based on load, reducing cost and the risk of processing delays
      Ease of integration
      Amazon Elastic MapReduce with Cascading allows data processing in the cloud without any changes to the underlying algorithms
      Flexible
      Hadoop with Cascading is flexible enough to allow “agile” implementation and unit testing of sophisticated algorithms.
      Adaptable
      Cascading simplifies the integration of Hadoop with external ad system
      Scalable
      AWS infrastructure helps reliably store and process huge (Petabytes) data setss
    • 29. Learning
    • 30. Thank you.

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