introduction to big data, march 2013
Post on 21-Oct-2014
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DESCRIPTION
Short presentation about big data explaining what it is and what are its marketing applications.TRANSCRIPT
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INTRODUCTION TO BIG DATAMARCH 2013
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“Humans now create in two days the same amount of data that it took from the dawn of civilization until 2003 to create”
Eric Schmidt, Google’s Executive Chairman
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Aggregate data Vs. Big data
Aggregate data
Big data
• What marketers & analysts have used for years• Maybe simpler, but you lose context
Loss of efficiency & money
• A single platform to track every user interaction• More complicated to implement
Better understanding of interactions & optimized actions
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DATA INFRASTRUCTUREDATA COLLECTION
A few massive players
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A few massive players
Data infrastructure
Solutions for companies
• Data acquisition • Data storage & organization
Data analysis
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A few massive players
Data collection
Solutions for companies
• Data acquisition• Consumer behavior analysis
Targeted advertising
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The button ‘Like’ has been hit 1.13 trillion times
17 billion location-tagged posts, including check-ins
1.06 billion monthly active users680 million mobile monthly active users
210,000 years of music have been played
$5.1 billion in revenue in 2012 $5.32 in average revenue per user
Connections between Facebook members
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Google Search20 billion pages indexed daily3,3 billion requests every day (40 000/sec)
Google +250 million members
Gmail425 million users
Android500 million users on Google’s mobile OS
Google Chrome1st browser worldwide37% of market share
Youtube800 million users4 billion hours of video watched monthly72 hours of video uploaded every minute
One of Google’s data centers
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CUSTOMIZATIONPREDICTION
Two appealing opportunities
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More efficient advertising
• More & more accurately targeted • In real time
Customization
Two appealing opportunities
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Two appealing opportunities
Customization
Tailored services & goods
• Ever narrower segmentation of customers • More knowledge on product usage
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Two appealing opportunities
Prediction
Thanks to iterative models, programs can learn new probabilistic associations over time
• Accurate detection of behaviors, patterns• Prediction of future events, trends
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Two appealing opportunities
Prediction
Applications
• NY Times archives to predict future disease outbreaks, riots & deaths• Amazon’s tools to recommend more purchases or to stop the forgetful
ones from buying the same book they purchased five years ago
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DATAVIZWEARABLE TECH
What’s next ?
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Data viz
What’s next ?
David McCandless
Dataviz
To make this amount of data understandable
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What’s next ?
Wearable tech
• Google Glass & the ‘talking shoe’ project• Nike+ FuelBand to track daily activity• Oakley Airwave to provide real-time feedback to skiers
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What’s next ?
Hyper-rationalism & magical experiences