Your SlideShare is downloading. ×
0

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Understanding Player Behaviour

1,681

Published on

An introduction to analytics, map/reduce and DynamoDB on AWS. Slides from the 'Powering games with Amazon Web Services' event in London.

An introduction to analytics, map/reduce and DynamoDB on AWS. Slides from the 'Powering games with Amazon Web Services' event in London.

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,681
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • \n
  • Transcript

    • 1. UnderstandingPlayer Behaviour
    • 2. Player behaviour is priceless
    • 3. Play statistics
    • 4. Social graph
    • 5. Monitor and iterate
    • 6. Increase playability
    • 7. IncreaseDLC sales
    • 8. Increase advertising engagement
    • 9. Ask questionsof player behaviour
    • 10. Ask questionsof player behaviour data
    • 11. Step 1: data collection
    • 12. Database
    • 13. Player data is complex
    • 14. Player data is plentiful
    • 15. Player data is fast moving
    • 16. Capturing andmanaging player data is hard
    • 17. Database canbecome bottleneck
    • 18. DynamoDB
    • 19. Step 2: analytics
    • 20. Hadoop
    • 21. Elastic MapReduce
    • 22. Managed
    • 23. Flexible
    • 24. Java(or Ruby, Python etc)
    • 25. Data warehouse
    • 26. S3Input data
    • 27. S3 Input dataCode Elastic MapReduce
    • 28. S3 Input dataCode Elastic Name MapReduce node
    • 29. S3 Input dataCode Elastic Name MapReduce node Elastic cluster
    • 30. S3 Input dataCode Elastic Name MapReduce node HDFS Elastic cluster
    • 31. S3 Input dataCode Elastic Name MapReduce node Queries HDFS + BI Via JDBC, Pig, Hive Elastic cluster
    • 32. S3 Input dataCode Elastic Name Output MapReduce node S3 + SimpleDB Queries HDFS + BI Via JDBC, Pig, Hive Elastic cluster
    • 33. DynamoDB integrateswith Elastic MapReduce
    • 34. Combine
    • 35. HiveQL queries
    • 36. Backup and restore
    • 37. Data movement
    • 38. Import/Export
    • 39. Multipart upload
    • 40. Multipart, parallel results delivery
    • 41. Direct Connect
    • 42. Scale control
    • 43. Resize running job flows
    • 44. 14 hoursTime remaining: 14 hours
    • 45. 14 hoursTime remaining: 7 hours
    • 46. Time remaining: 3 hours
    • 47. Balance cost and performance
    • 48. Resize based on usage patterns
    • 49. Steady state Steady state Batch processing
    • 50. Perfect for Spot
    • 51. Cluster types
    • 52. Small
    • 53. High memory High CPU or both
    • 54. HPC
    • 55. Click stream analysis for Best Buy 3.5 billion records 71 million unique cookies 1.7 million targeted ads 13 Tb of clickstream logs Each day
    • 56. Click stream analysis for Madden Workflow time from 2 days to 8 hoursProcurement time from 2 months to 5 minutes $13k per month500% increase return on advertising spend
    • 57. Web log analysis and recommendation engine $29.9 million in sales 842 million page views 434 Gb of page logs 97 million ‘favourites’

    ×