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Big Data Now: Current Perspectives from O'Reilly Radar
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This collection represents the full spectrum of data-related content we’ve published on O’Reilly Radar over the last year. Mike Loukides kicked things off in June 2010 with “What is data science?” and from there we’ve pursued the various threads and themes that naturally emerged. Now, roughly a year later, we can look back over all we’ve covered and identify a number of co
...moreebook, 137 pages
Published
(first published August 1st 2011)
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Aug 20, 2013
Richard Magahiz
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data scientists
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read-in-2013
Series of short form essays and interviews circa 2010, still relevant. Most of the links still work at the current time, which is worth something. It is a mix of big picture and details of implementations which may no longer be current, discussed at a level where one does not need to be an insider to understand the gist of the subjects. It served as a useful guide to the architecture behind the largest fixtures in the Big Data space though of course it leaves out the ones who have only made a na
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This, although a bit dated, is a really good primer into the terminology, challenges and excitement of "big data". It's available as a free PDF download. There are a lot of adverts in amongst the text, and they're all for a conference that has already been and gone. Whilst annoying, it was a free download, so I don't feel I can really complain. I now subscribe to a filtered O'Reilly Radar feed looking for big data related articles to continue my learning
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Interesting series of interviews and essays about what big data holds in store for people. It was bit fragmented, and some essays were really jargony, but perhaps the state of big data itself: no one is quite sure whats going on. In some sense though, it's a perfect way to understand what is going on in this rapidly evolving concept.
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Read the first 1/3 if you don't already know the jargon.
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“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it — that’s going to be a hugely important skill in the next decades.”
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“Making data tell its story isn’t just a matter of presenting results; it involves making connections, then going back to other data sources to verify them.”
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