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Ah yes, "the power of a society based on 10 times as much data". The best examples that the authors could come up with are: * A professor receiving an automati

Ah yes, "the power of a society based on 10 times as much data". The best examples that the authors could come up with are: * A professor receiving an automatic notification about when his flight was delayed. This saved him approximately 2 minutes as compared to checking the flight number before he left for the airport. * Stephen Wolfram figuring out what time he likes to send emails. Big data proponents need to tell a better story about how data will empower the individual. So far it seems like it's just about large corporations engaging in cross-merchandising, advertisers getting you to click on things, and spy agencies building dossiers without all that pesky legwork.

TallGuyShort 13y ago
I quite agree! I enjoyed this story along those lines a while back: "The best minds of my generation are thinking about how to make people click ads. That sucks." -- http://www.businessweek.com/magazine/content/11_17/b4225060960537.htm http://www.businessweek.com/magazine/content/11_17/b42250609...
taliesinb 13y ago
There's a really rich set of analyses in http://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/ http://blog.stephenwolfram.com/2012/03/the-personal-analytic... . "Times he likes to send emails" is a poor description for that body of work [I know the people who worked on it, and they worked hard and smart on it for a long time]. While I like neither buzzword, "data science" is probably better than "big data", for the following reasons: 1. not all data needs to be big to be interesting 2. the majority of 'science' that is typically done on data, both by enthusiasts and corporations, is both stereotyped and shallow. it won't be long before this is disrupted. unfortunately "big data" makes it sound like the problem is an engineering one -- in reality, the problem is cultural. 3. like 'traditional' science, data science is irreducibly hard. You need to be smart, creative, to know a diversity of methods, and you need interactive tools that allow you to explore and test hypotheses.

TallGuyShort 13y ago

I quite agree! I enjoyed this story along those lines a while back: "The best minds of my generation are thinking about how to make people click ads. That sucks." -- http://www.businessweek.com/magazine/content/11_17/b4225060960537.htm http://www.businessweek.com/magazine/content/11_17/b42250609...

taliesinb 13y ago

There's a really rich set of analyses in http://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/ http://blog.stephenwolfram.com/2012/03/the-personal-analytic... . "Times he likes to send emails" is a poor description for that body of work [I know the people who worked on it, and they worked hard and smart on it for a long time]. While I like neither buzzword, "data science" is probably better than "big data", for the following reasons: 1. not all data needs to be big to be interesting 2. the majority of 'science' that is typically done on data, both by enthusiasts and corporations, is both stereotyped and shallow. it won't be long before this is disrupted. unfortunately "big data" makes it sound like the problem is an engineering one -- in reality, the problem is cultural. 3. like 'traditional' science, data science is irreducibly hard. You need to be smart, creative, to know a diversity of methods, and you need interactive tools that allow you to explore and test hypotheses.