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Big data little devices презентация
Содержание
- 1. Big data little devices
- 2. WHAT IS BIG DATA? 0 - 2003 5 exabytes 2011 2.5 exabytes per day
- 3. PERSPECTIVES 1MB 1GB 1TB 2PB 5EB
- 4. WHERE’S IT COMING FROM? Source: domo.com 2012
- 5. WHAT DOES IT LOOK LIKE?
- 6. DEFINITIONS Big Data: unstructured data, don’t know
- 7. WHY NOW? 2003: Doug Cutting &
- 8. MAP REDUCE Traditional / Sequential Map Reduce
- 9. SPARK x 100 Map Reduce
- 10. CASES WHAT IT WILL DO TO US
- 11. SECURITY - PRIVACY NSA PRISM
- 12. PROFILING
- 13. VULNERABILITY Target Home Depot Michaels Blue Cross Blue Shield Sony Entertainment
- 14. SOCIETY
- 15. COMMERCE AMAZON DASH
- 16. COMMERCE AMAZON
- 17. CASES WHAT IT WILL DO FOR US
- 18. SPORTS SABERMETRICS (MONEYBALL)
- 19. PRODUCTIVITY GOOGLE NOW
- 20. POLITICS OBAMA CAMPAIGN 2012
- 21. SCIENCE MONTEREY BAY AQUARIUM RESEARCH INSTITUTE
- 22. HEALTH APPLE RESEARCH KIT The early partners
- 23. 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
- 24. ?
Слайд 6DEFINITIONS
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
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
Слайд 7WHY 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
2008: Yahoo open sources Hadoop, Apache Software Foundation
2009: Matei Zaharia starts Spark at UC Berkley
2013: Spark open sourced under Apache
Слайд 22HEALTH
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.
Слайд 23MORE 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
