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Big data tokyo (extended version)

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Presentation given to the Nikkei BP event on Big Data and Analytics in Tokyo, Japan on April 9, 2013.

Presentation given to the Nikkei BP event on Big Data and Analytics in Tokyo, Japan on April 9, 2013.

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Big data tokyo  (extended version) Big data tokyo (extended version) Presentation Transcript

  • DATA ANDDISILLUSIONMENTSOLVEforINTERESTINGOTHERWISE LIFE IS DULL.
  • Volume (the “big” part) Pick any Velocity two Variety(the “fast” (the part) “anything” part)
  • Big Data is the Third Age of computing Computing Networking Big Data Automate Interconnect Predict & change things things things (Jim Stodgill of O’Reilly Radar said this.)
  • Enterprises expect Big Data to deliver betterdecisions and improved customer experiences What tangible benefits do you hope to achieve through your big data initiatives? NewVantage Partners LLC www.newvantage.com
  • (And apparently Hadoop is winning) What data management approaches are you considering? NewVantage Partners LLC www.newvantage.com
  • Therelationaldatabaseis a general-purposetool.
  • A library is a database optimized for retrievalPhoto by cybrgrrl (http://www.flickr.com/photos/cybrgrl/1295482521/) on Flickr
  • A changecounter is adatabaseoptimized forinsertion
  • An example:eventualconsistency
  • “End of Day Balance will only appear for dates previous tothe last 2 business days.”“Transactions from today are reflected in your balance, butmay not be displayed on this page if you recently updatedyour bankbook, if a paper statement was recently issued, orif a transaction is backdated. These transactions will appearin your history the following business day.”
  • Relational BIG Statistical
  • http://www.flickr.com/photos/jenny-pics/3239638494/sizes/l/ Breadcrumb trail
  • The average enterprise has 178 socialmedia accounts (According to @setlinger and the Altimeter group.)
  • Ward off disease. Pinpoint disasters.A force Reveal corruption.for good. Make cities smarter. Improve how we teach.
  • Big healthcare
  • Big philanthropy
  • Big commuting
  • Erode our privacy. Justify prejudices.A force Polarize groups.for bad. Leak private truths.
  • Big prejudice
  • “…nobody notices offers they do notget. And if these absent opportunitiesstart following certain social patterns(for example not offering them tocertain races, genders or sexualpreferences) they can have a deep civilrights effect.” Anders Sandberg, Oxford University
  • Personalization looks a lot like prejudice.
  • Big radio
  • Times a song in “heavy rotation”is played each day30 Every 55m15 Every 4h0 2007 2012
  • Humans are bad at data.
  • We prefer false positives.
  • Wooly mammothhttp://www.flickr.com/photos/pong/172438102/sizes/o/
  • Sun templehttp://www.flickr.com/photos/30787002@N02/3298693694/sizes/l/
  • Some proof.
  • It’s really hard to find people who can thinkabout data well How challenging is it to source data scientists? NewVantage Partners LLC www.newvantage.com
  • Mistake correlation for causalitySeek truthiness rather than factFind patterns where they don’t existEasily swayed by toneSide with our tribesDig in and ignore new evidence
  • Athenian swimming pools
  • Volume BigVariety Data Good dataVelocityVeracity
  • 525,000 state & local officersUnder 25 officers per precinct130 million incident reports200,000 uses of force31% keep computer files
  • Evidence.com
  • Hard drive
  • Big Data is not about data.
  • Big Data is about truth,auditability, and the ability to analyze data on a level playing field. It’s about analysis for everyone.
  • Alistair Croll @acroll www.solveforinteresting.comTHANKS! alistair@solveforinteresting.comSOLVEforINTERESTINGOTHERWISE LIFE IS DULL.