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The Mythology of Big Data

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Keynote presentation on some of the assumptions about "big data" and how we use information in organizations, given at the O'Reilly Strata conference, February 2011 …

Keynote presentation on some of the assumptions about "big data" and how we use information in organizations, given at the O'Reilly Strata conference, February 2011

Video can be viewed on YouTube at http://www.youtube.com/watch?v=HwVPxYWDO4w

Note: I had to cut the story about payment and whiskey for time, which is what the video reference to booze is about.

Slide 22 is where the embedded video is located if you want to watch it here.

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  • 1. The Mythologyof Big DataO’Reilly Strata ConferenceFebruary 2, 2011Mark R. Madsenhttp://ThirdNature.net@markmadsen
  • 2. !"#$%&#()*+,+-%&(.$$/#0&1/)/*&/0#,2&)#&0##30&+2&/0&+1*&3#0$4(5+*6&
  • 3. 7+3#&/0&.&(+88+3/%& http://www.flickr.com/photos/ecstaticist/1120119742/
  • 4. 9).:0&)#&(#*$.,&8%)&4*3#$,%/*-&;/-&3..<&
  • 5. =)#&8%)&).&3$+"#&)#&-+,3&$40)& All we need is a fat pipe and pans working in parallel…!"#$%&()*$($"+)$,-$%.()$/01&2$1&+"#)&$"1&*+32$("1$4"(*5 $
  • 6. !"+,45+*&+2&3..&!"#$%"#&()*))#+,-(./*0"#$1"#&()*))#23+,-(./*4"#$""#&()*))#)##5*6"7"#8&()*))##.2#*,)*56&*$+*4$71$+*8"4#."($03$0($,#30(*33$31+#%1#+*$(7$9+"%*33*3$(7$&"/$1&*-$#3*$0(:"+;."(5$
  • 7. !"#$%)/*-&/0&0+&3/>#$#*&*+1?&Your grandmother, the data scientist.
  • 8. @.*%&(4$$#*&.AA$+.()#0&8/00&)#&A+/* & B0/*-&C/-&D..&
  • 9. E:0&*+&.;+4&F;/-G & B0/*-&C/-&D..&And “big” is often not as big as you think it is.
  • 10. E:0&*+&$#.,,%&.;+4&3..H&#/)#$ & B0/*-&C/-&D..&If there’s no process for applying information in a specificcontext then you are producing expensive trivia.
  • 11. 9)#$#&3+#0&)#&".,4#&/*&3..&(+8#&2$+8<& 9-,:-#*-;.#<==-=$()*) 2.#<=5##5#>*?<#*,)=#@)*5# *-<="/$%($/*$#3*$ 0(:"+;."($1"$0;9+"8*$ 1&*$7*%030"(3$;7*$0($"#+$ "+)(0>."(?@$ A5=55(*-;-/.#-=*?)* #<=B.@),@32)((5/<#<-= :)C<=B5=D*3>*?5B,-.+E F,B)=<G)D-=##55:*- ):+@<;3<==)*5(5/<#<-= :)C<=BH)I#E
  • 12. D#(/0/+*I8.J/*-&$#.,/5#0&J?5-+5,)D=B:-(5@<=#5=<-,:)=)B5:5=*<#+,<:),<@3<=*.<D-=)=(+)K5,=$2)#5(EJ?5:-(5;-,:<((@5:)=)B5:5=*<#+-@<D/)@>2.,5)./,)D/EL5I()*)<#(5#*)2<@<G<=B>I?</?<#I?33-.:)3?<*)I)@@*,3<=B*-+.#?3-.,()*)$(,<M5=)B5=()EN)*)<#/-=*5O*.)@>#-I5=55(#*-,<5#*-5O+@)<=?-II5*?<=C*?5I-,@(I-,C#>I?3:3()*)<#25K5,*?)=3-.,#>)=(I?33-.,*?5-,3#./C#EP-B=<DM52<)#/,5)*5#):-,)##;-,<=*5,+,5*)D-=E
  • 13. K&"#$%&.;0$.(&;40/*#00&/*#,,/-#*(#&8+3#, &A?-),5*?5+5-+@5:)C<=B(5/<#<-=#Q R*,)*5B</ J)/D/)@ F+5,)D-=)@
  • 14. 9).&/0&)#&*.4$#&+2&)#/$&3#(/0/+*0<& R/-+5>D:5;,):5-;(5/<#<-=>D:5#/)@5-;()*)>()*) M-@.:5>2,5)(*?-;()*)>;,5S.5=/3>+)K5,=M#;)/*$2)#5( R*,)*5B</ T-=*?# U! L.M#$*$2)#5( U! C$+.3&0(+A#&Analytic complexity U! N.(I;.0#3& N)3#$ U! @+3#$.#& J)/D/)@ A55C# 0(+A#& T<=#$ U! O4,#I;.0#3& N)3# U! P.$$+1&0(+A#& F+5,)D-=)@
  • 15. =)#&A$+(#00&.0A#(&+2&3#(/0/+*0&5#0&+&A#+A,#&R/-+5-;/-=*,-@;-,+5-+@5<=:-#*-,B)=<G)D-=#)@<B=#&<=+,-/5##>-=+,-/5##>-M5,+,-/5## R*,)*5B</ J)/D/)@ F+5,)D-=)@The exceptions not handled at one level due to rule /procedure / policy deficiency are escalated to the next.
  • 16. 9).&J/*3&+2&04AA+$&3+&)#%&)."#&+3.%<& R*,)*5B</ Other people J)/D/)@ Email, meetings Reports, dashboards F+5,)D-=)@ Realm of traditional BIReality of most reports and dashboards is that theyprovide basic monitoring at best.
  • 17. Q+1&.*3&1)#$#&(.*&%+4&.AA,%&3..&0+,45+*0<& V<B?#<=B@5M)@.5>@5## ;,5S.5=*>#-<:+,-M5*?5 R*,)*5B</ 5W5/DM5=5##-;<=(<M<(.)@Analytic complexity (5/<#<-=#E J)/D/)@ A#>>-$;0774*$)+"#(7$ X-I#<=B@5M)@.5>;,5S.5=*> /)=<:+,-M5*?55Y/<5=/3 F+5,)D-=)@ -,*?55W5/DM5=5##;-,@),B5 )BB,5B)*5<:+,-M5:5=*E
  •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
  • 19. !"#$%&#()*#*%#+,#(#-(*(#./0,)1.*2#%3#+&04-#.%5(3,#*%#.&66%3*#*7,82#3,(-#*70.#6(6,3#X$4(4$#& # !>+$& A0)#+*C$D0+"440$(7$E+72$FGGH$
  • 20. ]*--@:)C5,#.//55(#)#>)=(-=@3)#>*?5#3*+3$-;?<#*--@##.//55(I<*??<#)<(EV-I5M5,#?<=<=B*?52@)(5>?-I5M5,^5I5@5(*?5?<@*>?-I5M5,+5,;5/**?5?5_>)#I-,(<#*5#*5(-=@323/.`=BEJ?)*#I-,(#:<*?<##.//5##;.@I?-#5/@<5=*#(<5-;-@()B5Ea $ A+*7*+0%I$J+""I3
  • 21. About the Presenter Mark Madsen is president of Third Nature, a technology research and consulting firm focused on business intelligence, analytics and performance management. Mark is an award-winning author, architect and former CTO whose work has been featured in numerous industry publications. During his career Mark received awards from the American Productivity & Quality Center, TDWI, Computerworld and the Smithsonian Institute. He is an international speaker, contributing editor at Intelligent Enterprise, and manages the open source channel at the Business Intelligence Network. For more information or to contact Mark, visit http://ThirdNature.net.
  • 22. About Third NatureThird Nature is a research and consulting firm focused on new andemerging technology and practices in business intelligence, dataintegration and information management. If your question is related to BI,open source, web 2.0 or data integration then you‘re at the right place.Our goal is to help companies take advantage of information-drivenmanagement practices and applications. We offer education, consultingand research services to support business and IT organizations as well astechnology vendors.We fill the gap between what the industry analyst firms cover and what ITneeds. We specialize in product and technology analysis, so we look atemerging technologies and markets, evaluating the products rather thanvendor market positions.