The document discusses how software is increasingly being used to collect and analyze data, with data becoming more valuable than the software itself. It outlines the four stages of software production and how companies have transitioned from selling software to using it to collect customer data and generate insights. New technologies like Hadoop and NoSQL databases are enabling companies to more easily capture, store and analyze large volumes of user data. Data is the new differentiator as companies look to engage customers and gain insights from their behaviors online.

1. Software is Eating The World
But Data is Digesting It
10.20.2005
Dreamforce 2013

2. Software is Eating the World
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3. 3

4. 4

5. Source: PwC
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6. All were founded
before 1989
6

7. The average age of the
Top 20 Software Companies is
47 years
7

8. Software sales growth
is slowing
8

9. The Four Stages of
Software Production
9

10. STAGE 1
“The money is in the hardware,
not the software”
10

11. STAGE 2
“Actually, the money is in the software”
11

12. STAGE 3
“The money is not in the software,
but it is differentiating”
12

13. STAGE 4
“Software is not even differentiating,
the value is the data”
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14. The Age of Software
The Age of Data
14

15. Pressure is Growing
15

16. The Shock of The New
16

17. The CIO is the Last To Know
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18. Systems of Record
Systems of Engagement
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19. Engagement with customers,
partners, employees,
and other stakeholders
generates data
19

20. •
•
•
•
•
•
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Location, location, location
Influence patterns
Customer service feedback
Sentiment
Geographical trends.
Search Findings
Predicting retail and property sales
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21. Software is a means
21

22. “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
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23. 23

24. “In contrast to most traditional survey
methods, search data are collected as a byproduct of normal activity”
- the Bank of England
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25. 25

26. 26

27. 27

28. What you Share Changes What You Drink
28

29. When Web Companies Grow Up
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30. The Role
30

31. The 2013 Language Scape
31

32. The Trends
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33. 33

34. Source: John C. McCallum
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35. Many Tools – the Rise of Polyglot
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36. Database Types
Key Value Stores: RIAK, Redis, Voldemort,
Document databases: CouchDB, MongoDB
Column store – SAP HANA, Hbase, Vertica
Graph databases – Neo4J, Infinite Graph, Giraph
Column/Key Value Store Hybrid- Cassandra
Schemaless != Structureless
“Eventual Consistency” and CAP.
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37. Analysis Modes
37

38. The Players
38

39. Hadoop is Eating the World
39

40. Data Viz
D3.js
Processing.org
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41. GitHub Growth and the RedMonk Experience
See Story of Data post here.
41

42. Source: Google Trends
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43. Source: Google Trends
43

44. Source: Hacker News
44

45. Source: Hacker News
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46. Source: Stack Overflow
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47. Source: Stack Overflow
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48. 48

49. 49

50. 50

51. Social Coding
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52. Social Data
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53. Hadoop at Facebook
http://hadoopblog.blogspot.com/2010/05/facebook-has-worlds-largest-hadoop.html
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