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John Callery
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John Callery

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Podcast for the day: +Ford Motor Company's "Data Science Leader", +Michael Cavaretta, talks connected cars, dealer recommendation systems and hadoop (interview starts 18 minutes in). +GigaOM 
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John Callery

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Really great work on extracting value from old and challenging data sets, plus finding ways to create/combine new data to come up with some interesting conclusions.
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Catchy headline, but it sounds like more of a case of "maturing" and "focusing" than "shrinking" to me...

"In the case of Big Data, this probably means less focus on back-end technologies like new types of storage or database frameworks, and a rethinking about how best to integrate human knowledge, algorithms and diverse sets of data."
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+The Economist is having an interesting debate on cities' use of data and what value it can provide.
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Using social network analysis and language processing to predict gender, age and personality. The Time article focuses on gender stereotypes, but the full PLOS ONE article expands on a number of interesting methods and findings.
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Gender will soon be no longer relevant. A user will be identified by what they buy and what they sell. Sadly.
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John Callery

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This is a good look at an areas that can use a lot more focus on analytics, though I'm not sure why we're considered 'scary'... :-)
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Great projects like this help support the need for open data initiatives.
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John Callery

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Interesting look at 'closed' data sets and the implications for privacy, accuracy and peer review inside the walls of 'corporate science'. +WIRED 
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It would be interesting to compare this with LinkedIn information.
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John Callery

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Nice viz of TLDs
 
Geography of Top-Level Domain names.
This graphic maps a combination of generic top-level domains (gTLDs) and country code top-level domains (ccTLDs) in order to provide an indication of the total number of domain registrations in every country worldwide.

All gTLDs are mapped through an analysis of information returned by the WHOIS Internet protocol, that provides contact information for any given domain. For instance, this meant that for every .com domain name, the location registered in that domain’s WHOIS data was retrieved and stored in a database.

#domainnames   #map   #infographic  
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John Callery

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Great advice from a guy who knows what he's talking about when it comes to visualization.
 
My answer to What should everyone know about making good charts and graphs to represent data? http://qr.ae/IqOrc
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