the data game: visualizing ip & gambling data with quova
TRANSCRIPT
The Data Game
Visualizing IP & Gambling with QuovaGoogle TechTalk, Zurich
August 25, 2010
Introduction
• A bit about the two guys on stage
• What does Quova have to do with it?
• Objective: Big IP data and gambling - insights
Methodology
30 billion queries/month
Geographic Information Network Characteristics
Global Gambling: Log on, ante up.
• Growth Market– 8% of total market in 2009, with revenues of about $26 billion (H2)– Growth of 13% a year to $36 billion by 2012 (H2)– Mainly Europe and Asia
• U.S. legislation in the next 24 months– H.R. 2267 would legalize some forms of online gambling– A companion bill would allow the IRS to tax such activity– Could mean $42 billion for the government over 10 yrs. (NYTimes)
A Visualization Project
Two Kinds of Graphs
A short aside on Horizon Graphs
• Jeffrey Heer, Nicolas Kong, and Maneesh Agrawala, “Sizing the Horizon: The Effects of Chart Size and Layering on the Graphical Perception of Time Series Visualizations”
• Stephen Few (perceptualedge.com) • Panopticon• Let’s look: Horizon Graph
Horizon Graph Explained
Copyright © 2008 Stephen Few, Perceptual Edge
50 stocks between October 2005 and September 2006Copyright © 2008 Stephen Few, Perceptual Edge
Horizon Graph Explained
Copyright © 2008 Stephen Few, Perceptual Edge
50 stocks between October 2005 and September 2006Copyright © 2008 Stephen Few, Perceptual Edge
50 stocks between October 2005 and September 2006Copyright © 2008 Stephen Few, Perceptual Edge
Stream Graphs
“Stacked Graphs – Geometry & Aesthetics”by Lee Byron & Martin Wattenberg
http://www.leebyron.com/else/streamgraph/
The Online Gambling Industry
Fri Sat Sun Mon Tue Wed Thu Fri
Europe
Fri Sat Sun Mon Tue Wed Thu Fri
Everything but the UK
Fri Sat Sun Mon Tue Wed Thu Fri
Asia
Fri Sat Sun Mon Tue Wed Thu Fri
North America by Organization
Fri Sat Sun Mon Tue Wed Thu Fri
All but Europe, Asia, and N. America
Fri Sat Sun Mon Tue Wed Thu Fri
UK by City
Fri Sat Sun Mon Tue Wed Thu Fri
UK without London
Fri Sat Sun Mon Tue Wed Thu Fri
Germany by City
Fri Sat Sun Mon Tue Wed Thu Fri
Denmark by City
Fri Sat Sun Mon Tue Wed Thu Fri
Connection Types
Fri Sat Sun Mon Tue Wed Thu Fri
Mobile Carriers
Fri Sat Sun Mon Tue Wed Thu Fri
Dial-up Users by Country
Fri Sat Sun Mon Tue Wed Thu Fri
Anonymizer by Country
Fri Sat Sun Mon Tue Wed Thu Fri
Anonymizer by Carrier
Fri Sat Sun Mon Tue Wed Thu Fri
Where this goes from here
• We’re just starting• Make the data public• The data becomes dynamic
– Find trends– Predict and prevent fraud– Optimize advertizing– Predict traffic patterns and events– Confirm or disprove assumptions
[email protected] [email protected]@ptancredi @tobiassp