the data game: visualizing ip & gambling data with quova

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

perry@quova.com tobias@quova.com@ptancredi @tobiassp