Big data little devices

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Big data little devices what it will do to us and for us

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What is big data? 0 - 2003 5 exabytes 2011 2.5 exabytes per day

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Perspectives 1MB 1GB 1TB 2PB 5EB

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Where’s it coming from? Source: domo.com 2012

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What does it look like?

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Definitions Big Data: unstructured data, don’t know what questions are yet Business Intelligence: structured data, know what the questions you want answered Statistics: structured data, not realtime, no action taken as a result Machine Learning: creation of algorithms and applying them to data sets in an attempt to learn from data Predictive Analytics: extracting existing data to predict trends

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Why now? 2003: Doug Cutting & Mike Cafarella, Nutch 2004:Google Labs: Map Reduce 2006:Doug Cutting moves to Yahoo and creates Hadoop 2008: Yahoo open sources Hadoop, Apache Software Foundation 2009: Matei Zaharia starts Spark at UC Berkley 2013: Spark open sourced under Apache

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Map Reduce Traditional / Sequential Map Reduce

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Spark x 100 Map Reduce

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Cases What it will do to us

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Security - Privacy NSA PrISM

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Vulnerability Target Home Depot Michaels Blue Cross Blue Shield Sony Entertainment

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Commerce Amazon Dash

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commerce amazon

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Cases What it will do FOR us

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sports sabermetrics (moneyball)

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productivity google now

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POLITICS Obama campaign 2012

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Science Monterey bay aquarium research institute

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health Apple Research kit The early partners tell Bloomberg that they got thousands of volunteers within a day of launch, including 11,000 for a Stanford University cardiovascular trial -- for context, Stanford says that it would normally take a national year-long effort to get that kind of scale. The flood of data will theoretically improve the quality of the findings, especially since the automatic, phone-based tracking should prevent people from fibbing about their activity levels.

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more reading http://www.domo.com/blog/2014/04/data-never-sleeps-2-0/ http://www.redorbit.com/education/reference_library/general-2/history-of/1113190638/the-history-of-mobile-phone-technology/ http://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/ http://www.wired.com/2015/04/robots-roam-earths-imperiled-oceans/?mbid=nl_041315 http://www.allbusiness.com/what-does-your-supermarket-know-about-you-15611312-1.html http://www.geekwire.com/2015/baseball-analytics-mystery-mlb-team-uses-a-cray-supercomputer-to-crunch-data/ http://www.geekwire.com/2015/this-big-data-startup-just-raised-cash-to-analyze-driver-behavior-creating-safety-scores-for-individual-motorists/?utm_source=GeekWire+Daily+Digest&utm_campaign=20eb1892b3-daily-digest-email&utm_medium=email&utm_term=04e93fc7dfd-20eb1892b3-233387065&mc_cid=20eb1892b3&mc_eid=7b61e5049a http://www.newyorker.com/culture/culture-desk/the-horror-of-amazons-new-dash-button https://www.amazon.com/oc/dash-button http://harvardmagazine.com/2014/03/why-big-data-is-a-big-deal http://www.businessinsider.com/big-data-is-growing-thanks-to-mobile-2013-1http://venturebeat.com/2015/04/03/how-microsofts-using-big-data-to-predict-traffic-jams-up-to-an-hour-in-advance/ http://www.engadget.com/2015/04/13/ibm-watson-health-cloud/?utm_source=Feed_Classic_Full&utm_medium=feed&utm_campaign=Engadget&?ncid=rss_full

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