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Digital Paths and Digital Breadcrumbs:

          Social, Data Science and New Business Models

 10.20.2005
Digital London March 2012
Cloud is eating the World




          2
Source: John C. McCallum




3
Relentless


"@stoweboyd: Today’s basic Kindle costs
 80% less, weighs 40% less, 2/3 less space
 and holds 7x as many books as the
 original"




                   4
What do these companies
   have in common?

           5
6
They make up PwC's
Global Software Top 20


          7
Source: PwC



8
What else do they
have in common?

        9
All were founded
   before 1989


       10
1989 was 22 years ago



          11
Things that happened in 1989

  The Soviet Union left Afghanistan

  Time and Warner Merge

  The Exxon Valdez oil spill

  Tiananmen Square

  Rain Man won best picture


                12
The average age of the
Top 20 Software Companies is
          47 years


             13
That's partially skewed by the likes
    of IBM (1911) NEC (1899!)



                 14
Fewer outliers? 31 years


           15
16
17
18
19
20
Growth through software sales
         is slowing


              21
Growth through data is not



            22
The Four Stages of
Software Production


         23
STAGE 1




“The money is in the hardware,
      not the software”
              24
STAGE 2


“Actually, the money is in the software”



                   25
STAGE 3




“The money is not in the software,
     but it is differentiating”
                26
STAGE 4




“Software is not even differentiating,
       the value is the data”
                   27
Microsoft's Share Price




           28
The Age of Software        The Age of Data




                      29
Software is a means


         30
Engagement with customers,
   partners, employees,
  and other stakeholders
      generates data


            31
Systems of Record to
Systems of Engagement



         32
“The lumber industry sells what used to be
waste — sawdust, chips, and shredded wood
— for a pretty profit. Today you’ll find these
by-products in synthetic fireplace logs,
concrete, mulch, particle board, fuel, livestock
and pet bedding, winter road traction, weed
killing and more.”
                          Jason Fried, 37signals




                      33
•   Location, location, location
•   Influence patterns
•   Customer service feedback
•   Sentiment
•   Geographical trends.
•   Search Findings
•   Predicting retail and property sales



                      34
Right now, if you think of the data at
  all, you probably consider it a by-
               product




                  35
“In contrast to most traditional survey
methods, they [search data] are collected as a
by-product of normal activity”
           - the Bank of England




                        36
W not use it?
 hy


      37
Who’s already doing this?


            38
39
40
41
42
What you Share Changes What You Drink




                  43
RedMonk’s Developer Intelligence portal




                   44
45
A New Kind of Data “Store”




          46
Hadoop at Facebook
http://hadoopblog.blogspot.com/2010/05/facebook-has-worlds-largest-hadoop.html




                                                          47
So if you're in business
  and you're ignoring
Implicit and social data

           48
You're doing it wrong


          49
50
QUESTIONS

    51
LinkedIn Members




       52
GitHub Rankings
1.   Java (5)
2.   Scala (18)
3.   Clojure (22)
4.   Groovy (23)

               53
GitHub Change




      54
Ohloh Monthly Contributors




            55
Language Tiers




      56
For Example




     57
Photo credits
Breadcrumb – diongillard on Flickr
Pathway by ^riza^ on Flickr
SF in Cloud – SF Chronicle




                               58

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