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Big data little devices what it will do to us and for us
What is big data? 0 - 2003 5 exabytes 2011 2.5 exabytes per day
Perspectives 1MB 1GB 1TB 2PB 5EB
Where’s it coming from? Source: domo.com 2012
What does it look like?
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
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
Map Reduce Traditional / Sequential Map Reduce
Spark x 100 Map Reduce
Cases What it will do to us
Security - Privacy NSA PrISM
Vulnerability Target Home Depot Michaels Blue Cross Blue Shield Sony Entertainment
Commerce Amazon Dash
Cases What it will do FOR us
sports sabermetrics (moneyball)
productivity google now
POLITICS Obama campaign 2012
Science Monterey bay aquarium research institute
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.
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