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A non-technical introduction to Big Data that conveys the core concepts and ideas of big data without giving into the hype.
A non-technical introduction to Big Data that conveys the core concepts and ideas of big data without giving into the hype.
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See CAP theorem for more details http://www.julianbrowne.com/article/viewer/brewers-cap-theorem
http://www.fastcodesign.com/1671893/the-secret-sauce-behind-netflixs-hit-house-of-cards-big-data
http://en.wikipedia.org/wiki/Google_Traffic#Crowdsourced_traffic_data
https://twitter.com/BigDataBorat/status/372350993255518208
https://twitter.com/josh_wills/status/198093512149958656
Although use of the term data science has exploded in business environments, many academics and journalists see no distinction between data science and statistics. Writing in Forbes, Gil Press argues that data science is a buzzword without a clear definition and has simply replaced “business analytics” in contexts such as graduate degree programs.[13] In the question-and-answer section of his keynote address at the Joint Statistical Meetings of American Statistical Association, noted applied statistician Nate Silver said, “I think data-scientist is a sexed up term for a statistician....Statistics is a branch of science. Data scientist is slightly redundant in some way and people shouldn’t berate the term statistician.”[14]