BigQuery in Social Gaming

Yan Cui
Yan CuiSpeaker at Self
BigQuery in Social Gaming
Yan Cui, Senior Developer
Davinder Pank, Social BI Manager
Who is Gamesys?
• Founded in 2001
• #1 in the UK
• Handle $5 Billion in turnover annually
• First company to launch real money gaming on Facebook
• Employ 1,000 globally
BigQuery in Social Gaming
BigQuery in Social Gaming
BigQuery in Social Gaming
Travel, Collect, Craft!
Trap Monsters
BigQuery in Social Gaming
Events driven Analysis
Enables deeper ad hoc analysis
Analysis goes only as far as the data
Finer the grain, bigger the volume
Be Ready for Success
Jackpotjoy Slots Bingo Lane Here Be Monsters
DAU 600,000+ 150,000+ 40,000+
Events (monthly) 5 billion+ 500 million+ 700 million+
1 TB+ 200 GB+ 500 GB+
• Ensure the health of our defined KPIs across our products –
Jackpotjoy Slots, Bingo Lane and Here Be Monsters
• Develop player insights to better improve the depth with
which users engage with our games
Social Gaming Business Intelligence,
Gamesys
BigQuery
Why BigQuery?
Scales
Managed
Fully managed architecture,
allows instant project
startup, and rapid time to
insight
Easy to learn, minimal
transition period, especially
for those moving from
traditional relational
databases
SQL
Grows with your project,
scales horizontally from 100
thousands to 100 Bn's of
rows with no loss of
performance on interactive
queries
Monitoring KPI Health
Reporting
Apps Script Spreadsheets
Cloud
Storage
Big
Query
ETL
KPI Dashboards in Google Spreadsheets
Custom Dashboards in Google Spreadsheets
Developing Player Insights
Big Joins
No need for temporary
tables, let’s us get to the
results we need in as few
steps as possible
How BigQuery features and functions allow us to better
explore our data
Developing Player Insights
• Our analysis hinges on being able to compare behaviour amongst players
with similar in-game maturity to one another
• Where we gain some of our most invaluable insights are where changes in
player behaviour lie outside the norm of what we would expect
How BigQuery features and functions allow us to better
explore our data
Developing Player Insights
Window Functions
Rank and partition allow us
to compare fairly player
engagement and
monetisation metrics across
players with the same in-
game maturity. Reduces
dependence on external
tools.
Lead and lag allow us to
easily identify segments
exhibiting interesting
changes in behaviour
How BigQuery features and functions allow us to better
explore our data
Reporting
Apps Script Spreadsheets
Cobra
App
Engine
Cloud
Storage
Big
Query
ETL
Mailman
App
Engine
email
mobile push
notifications
4
facebook
notifications
Beyond BigQuery
In the near future..
• Move from nightly ETL to real-time
– BigQuery streaming insert
• Predication API
Thank You!
JackpotJoy Slots
http://apps.facebook.com/jackpotjoyslots
Bingo Lane
http://apps.facebook.com/bingolane
Here Be Monsters
http://apps.facebook.com/herebemonsters
Building a MMORPG
http://bit.ly/1hjqoL8
http://slidesha.re/18MD4XY
Google I/O 2013 – Here Be BigQuery
http://bit.ly/1fHjbce
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BigQuery in Social Gaming

  • 1. BigQuery in Social Gaming Yan Cui, Senior Developer Davinder Pank, Social BI Manager
  • 2. Who is Gamesys? • Founded in 2001 • #1 in the UK • Handle $5 Billion in turnover annually • First company to launch real money gaming on Facebook • Employ 1,000 globally
  • 9. Events driven Analysis Enables deeper ad hoc analysis Analysis goes only as far as the data Finer the grain, bigger the volume
  • 10. Be Ready for Success Jackpotjoy Slots Bingo Lane Here Be Monsters DAU 600,000+ 150,000+ 40,000+ Events (monthly) 5 billion+ 500 million+ 700 million+ 1 TB+ 200 GB+ 500 GB+
  • 11. • Ensure the health of our defined KPIs across our products – Jackpotjoy Slots, Bingo Lane and Here Be Monsters • Develop player insights to better improve the depth with which users engage with our games Social Gaming Business Intelligence, Gamesys BigQuery
  • 12. Why BigQuery? Scales Managed Fully managed architecture, allows instant project startup, and rapid time to insight Easy to learn, minimal transition period, especially for those moving from traditional relational databases SQL Grows with your project, scales horizontally from 100 thousands to 100 Bn's of rows with no loss of performance on interactive queries
  • 13. Monitoring KPI Health Reporting Apps Script Spreadsheets Cloud Storage Big Query ETL
  • 14. KPI Dashboards in Google Spreadsheets
  • 15. Custom Dashboards in Google Spreadsheets
  • 16. Developing Player Insights Big Joins No need for temporary tables, let’s us get to the results we need in as few steps as possible How BigQuery features and functions allow us to better explore our data
  • 17. Developing Player Insights • Our analysis hinges on being able to compare behaviour amongst players with similar in-game maturity to one another • Where we gain some of our most invaluable insights are where changes in player behaviour lie outside the norm of what we would expect How BigQuery features and functions allow us to better explore our data
  • 18. Developing Player Insights Window Functions Rank and partition allow us to compare fairly player engagement and monetisation metrics across players with the same in- game maturity. Reduces dependence on external tools. Lead and lag allow us to easily identify segments exhibiting interesting changes in behaviour How BigQuery features and functions allow us to better explore our data
  • 20. In the near future.. • Move from nightly ETL to real-time – BigQuery streaming insert • Predication API
  • 22. JackpotJoy Slots http://apps.facebook.com/jackpotjoyslots Bingo Lane http://apps.facebook.com/bingolane Here Be Monsters http://apps.facebook.com/herebemonsters Building a MMORPG http://bit.ly/1hjqoL8 http://slidesha.re/18MD4XY Google I/O 2013 – Here Be BigQuery http://bit.ly/1fHjbce