Big Data                 + Social                 + Games                 @Is Cool                        16/03/2012TITRE ...
Who is IsCool Entertainment?  Social game publisher based in    Agenda  Paris, France                     • What do we do?...
Is Cool Games                              IsCool,   Absolute Solitaire,                Delirious Collectible   The best s...
Games & Virtual Goods                         Play the Game & Gain some                         virtual goods             ...
Virtual Goods  Virtual Economy  Virtual Goods Must not be too  easy to get  The game would not be fun !  No monetizatio...
Why is this Big Data ?                           Number of object transactions per day                           NYSE    ...
The Real Big Data Challenge  Collaborate for collective insights                                                        Pr...
Specifics of Game Analytics  Virtual Goods  We are the Factory AND the    Shop, and most of the products    are free.  So...
Use Case 1 : Understanding Users  1: Defining engagement                                        Tenure length             ...
Case Study 1 - Segment User Behaviours  2: Describing engagement patterns: Running a segment analysis
Use Case 2 : Understanding Users as a whole  10 Million Nodes  Around 1 000 Billion  Edges                               H...
Understanding Users as a WholeLots of small clusters ((mostly 2players)                                              Some ...
Use Case 3 : Analyze Long Terms effect of a feature                             A/B Tests                             Som...
… Howover the last 3 years   Analyzing the Offer• Tools changed         • Online Analytics Platform• Scale changed        ...
What we learned         Diversity                  Relativity                    Superciality• Theres no Hadoop+R       • ...
Mixed Approach  SaaS Analytics Platforms  For common, business metrics (virality,     traffic, engagement)  Corporate Le...
Datawarehouse for the Big Data era   Hadoop/Hive (through Amazon’s                   Open Source ETL (PyBabe)   Elastric M...
Questions ?
Upcoming SlideShare
Loading in...5
×

Big data paris 2011 is cool florian douetteau

884

Published on

Big data, HADOOP, Florian Douetteau, isCool Entertainment, BI, SQL, Big Data Congress

1 Comment
2 Likes
Statistics
Notes
No Downloads
Views
Total Views
884
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
13
Comments
1
Likes
2
Embeds 0
No embeds

No notes for slide

Big data paris 2011 is cool florian douetteau

  1. 1. Big Data + Social + Games @Is Cool 16/03/2012TITRE DOCUMENT
  2. 2. Who is IsCool Entertainment? Social game publisher based in Agenda Paris, France • What do we do? Social Gaming #1 French publisher in terms of • What kind of (Big) Analytics we do? audience (450k Daily Active Lots Users) & revenue • How we do it ? Hadoop, Python, R, Tableau, Geph and stuff… 2.8 Millions Fans 80 employees Florian Douetteau 9.1 million € revenue in 2010 CTO 4 live applications on Facebook @fdouetteau
  3. 3. Is Cool Games IsCool, Absolute Solitaire, Delirious Collectible The best solitaire game Game available online Temple Of Mahjong, Belote Multijoueur, Collect, Play, Exchange Play, Win, Meet
  4. 4. Games & Virtual Goods Play the Game & Gain some virtual goods Play again & Gain more Collaborate with other players & Gain More …. Possibly buy  To grow quicker  To help others
  5. 5. Virtual Goods  Virtual Economy Virtual Goods Must not be too easy to get  The game would not be fun !  No monetization Virtual Goods must not be hard to get  People would churn because of Let’s Trade 1 Watch against frustration ! 3 Hammers Virtual Goods can be usually traded between players Virtual and actual “Price” of a good
  6. 6. Why is this Big Data ? Number of object transactions per day  NYSE 3,600,000,000 18 Million users generated actions per day  IsCool 2,150,000,000 7 Billions per year.  Nasdaq 1,600,000,000 9,8 TB Data to  Nikkey 1,500,000,000 analyze  Footsie 860,000,000  CAC 40 142,500,000
  7. 7. The Real Big Data Challenge Collaborate for collective insights Programmers’ Perspective : Game Designer Perspective : Log Files & Work ? Nice Charts ? Realtime? what metrics? data scientist?BI Veteran: Business Guy Perspective:Schema Definition ? Revenue Forecast ?
  8. 8. Specifics of Game Analytics Virtual Goods  We are the Factory AND the Shop, and most of the products are free. Social Networks  Network effects are key Games  The product changes EVERY day !  Sudden wage of unexpected players from Guatemala !  People try to cheat !
  9. 9. Use Case 1 : Understanding Users 1: Defining engagement Tenure length Visit frequency Virality Traffic Key drivers??? Paying user conversion ARPPU Score Use of feature A,B,C…
  10. 10. Case Study 1 - Segment User Behaviours 2: Describing engagement patterns: Running a segment analysis
  11. 11. Use Case 2 : Understanding Users as a whole 10 Million Nodes Around 1 000 Billion Edges How does the graph evolve in time ? What are the communities?
  12. 12. Understanding Users as a WholeLots of small clusters ((mostly 2players) Some mid size communities A very large community
  13. 13. Use Case 3 : Analyze Long Terms effect of a feature A/B Tests  Some features can be A/B tested  …and some cannot !  How to measure the uplift ? Are players using the new feature…  More engaged?  Generate more virality ?  etc…. Complexity  Multiple variable to observe (other features, history ) TITRE DOCUMENT 16/03/2012
  14. 14. … Howover the last 3 years Analyzing the Offer• Tools changed • Online Analytics Platform• Scale changed • Commercial / Open Source ETL• Focus Changed • Commercial BI Visualization Software • Commercial / Open Source databases (column stores) •…
  15. 15. What we learned Diversity Relativity Superciality• Theres no Hadoop+R • Windows / Linux ? Cloud • Ability to display is more Magic (Expertise, Entry or on-premise ? important than the Costs, Maintenance) • Do you have internal data result.• There’s no XYZ Magical mining experts (yes/no) ? Product • Do you have internal scalability experts (yes/no) ? • What is _real_ budget ? 0K ? 10K ? 100K ? 1000K ?
  16. 16. Mixed Approach SaaS Analytics Platforms  For common, business metrics (virality, traffic, engagement)  Corporate Level Visibility  Day-to-day Internal Datawarehousing  Detailed Business Metrics  Virtual Economy Modeling  Long term behaviours  Business Level Visibility  Week-to-Week Datamining tools  Ad-hoc analytics  Graph Analytics
  17. 17. Datawarehouse for the Big Data era Hadoop/Hive (through Amazon’s Open Source ETL (PyBabe) Elastric Map Reduce) • Pure Python ETL • Used to reduce the amount of information : • Good integration with AWS/ S3 10 GB a day => 1GB a day • Easy to integrate in our development • High cost of development for "business" environment related processing Columnar Database (Infinidb, Open Dashboarding (Tableau Software) Source) • +Direct connection to the database • Free (as beer) • +Excel fan biz guy can use it with no training ! • Good performance for analytics tasks on a few hundreds million lines ( SELECT … GROUP BY … ORDER … ) • Featured and limited performance compared to commercial Column Stores
  18. 18. Questions ?
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×