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Opportunities with Data Science

Ashiq Rahman, Ph.D.
Principal Strategy Planner, Fujitsu Network Communications
ashiqur@gmail.com

Tableau User Group, Dallas. October 29, 2013
$

Opportunities

Data

Insight

Action & automation

Grab the fortune !
1
$

About me: problem solver with technology
Ph.D, 1999
Quantum Optics

Early Big Data

Architected & built
simulation platform

Startup within
big company

B.Sc. (4.0 GPA)
Math & Physics
High school, 1988
2nd rank, nationwide

Statistical modeling
Wireless systems

System engineering

Network architecture

Strategy Planning

Network graphs
100G

Business development
Data science
2
$

About me: always learning

3
$

About me: Organize & DJ Tango events

4
$

About me: Host of Tango in Klyde Warren Park

http://www.facebook.com/tangointheparkdallas
5
$

Opportunities

What, why, how?
6
$

Trip to Disneyland!

7
$

Overview

Industry
examples
Demo/Tips

Future

Vision
DSS
Challenges

Fortune!

8
$

Data driven decision making

9
$

Scott Adam‘s take

10
$

Data driven decision making

Data not available on time
Decisions are delayed

Data not available/no access
Decisions are made with
assumptions & ‗gut feel‘.

11
$

Relying only on gut feel can backfire!

12
$

Empowerment of decision makers

Data not accessible in an easy manner.

Limited trends/patterns
analysis (‗food for
thought‘ for innovation).

Innovation
Not enough scorecards, KPIs …
13
$

Today …

or

Report table (pivot)

14
$

Vision – Decision Support System

―The system is not just about displaying reports,
but rather must be a platform for decision
making in the broadest sense‖
- Ralph Kimball, one of the original architects of Data Warehousing.

15
$

Inspiration
Zoom & Layer feature in Google maps

16
$

Decision Support System

17
$

Tips – server look customization

Customization supported by Tableau
http://onlinehelp.tableausoftware.com/current/server/en-us/help.htm#customize_namelogo.htm

18
$

Tips – server look customization

Unsupported
Hack!

C:Program Files (x86)TableauTableau Server8.0wgserverpublic

Replace this
(Back it up)
With this

favicon.ico should be 32x32 pixels
Go to: <ServerURL>/favicon.ico
Refresh in the browser

19
$

Business stories with data

20
$

Interactive geographical analysis

21
$

Tips – information layering

22
$

Relation & network graphs

Multiple platforms
23
$

Knowledge & wisdom !

‗Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?‘
T.S. Eliot, ―Choruses from The Rock‖ (1934)

―Knowledge is knowing that a tomato is a fruit;
wisdom is knowing not to put it in a fruit salad.‖
Brian O'Driscoll (2009) from Miles Kington

24
$

Visual analytics to wisdom !

Past
Sales

Bookings

Forecast

What is happening
now?

What will happen?

Reports

Insight

Future

What happened?

Data

Present

Alerts

How & why did it
happen?

What’s the next
best action?

Prediction

What’s the
best/worst case?

25
$

DSS: User experiences excitements!
―This is an awesome and valuable tool.‖
- Marketing

―It is extremely easy to navigate.‖
- Accounting

―It is like treasure hunt.‖
- Sales

―Haven‘t seen anything like this in my whole life !‖
- Planning
26
$

Recommendation from strategy leaders

―You got to make a decision support tool that the frontline users understands.‖
―The moment you make it simple & understandable, then people start using it
and you get better decisions.‖
http://www.mckinsey.com/features/advanced_analytics
27
$

Analytics to $:

Lead of analytical team
Internal data
analytics

Increased sales

Andrew Pole

―Between 2002 — when Pole was hired — and 2010,
Target‘s revenues grew from $44 billion to $67 billion.‖
http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all
http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did
28
$

Analytics to $:
How much is a mortgage contract worth? (mid 1990)
Public data

External valuation

Dan Steinberg

Internal data
& analytics

Better valuation

Hold
or
Sell

?

Additional $600* million in profit during the first year alone!
*($800 million today).

http://www.linkedin.com/groups/Chase-Banks-Big-Win-Predicting-1005097.S.177355288
29
$

Visualization to ―control of spreadsheets‖

JPMorgan lost more than $6B in 2012 due to
―deficiencies found in the internal control environment, ...
and lack of control over spreadsheets ..‖

http://en.wikipedia.org/wiki/JPMorgan_Chase
30
$

‗Big data, analytics & the path from insights to value‘

―Top performers say Analytics is a key differentiator‖

―Organizations expect that the ability to visualize data
differently will be the most valuable technique‖

http://sloanreview.mit.edu/article/big-data-analytics-and-the-path-from-insights-to-value/
31
$

Analytics trumps intuition

Top performing companies use
analytics more than intuition.

A likelihood of 1.0 indicated an equal likelihood that the organizations will use either analytic or intuition.
32
$

Where analytic work done

Analytics migrate toward more centralized units,
first at the local line of business and then at the enterprise level.
33
$

What it takes: Information visualization

34
$

What it takes: Aesthetics & design

http://www.ideo.com

35
$

What it takes: expertise in many areas
Business, process,
technology

Finance,
accounting

High level analytics
& platforms

Vision

―Data Science‖
IT Hacking!

Develop
Design &
aesthetics

Deliver

Information
visualization

Problem solver
Agile, curious

Human psychology
(story telling, …)
36
$

What it takes: Data science

http://en.wikipedia.org/wiki/Data_science
37
$

Imagine in future …

It‘s not science fiction anymore!

Inspiration movie:
―Minority report (2002)‖

38
$

Science fiction, not anymore !

39
$

2012 Election results prediction

#NateSilverFacts
•

If you liked Chuck Norris facts, you'll love Nate Silver facts!

•

When Nate Silver asks you "Wanna make a bet?" The
correct answer is no.

•

Nate Silver doesn't "crunch" numbers. Numbers
disintegrate in fear before him.

•

Outliers exist because they're hiding from Nate Silver.

40
$

Google‘s self-driving car

41
$

Self-driving car: ―Look Ma, no hands!‖

42
$

Self-driving car: pattern recognition & action

Similar technology can be
used in many areas.

43
$

IBM Watson competes Jeopardy & wins!

44
$

IBM Watson as doctor‘s aid

Utilization management decisions
in lung cancer treatment.

90% of nurses in the field who use Watson now follow its guidance.

45
$

IBM‘s Smarter Planet

http://www.youtube.com/watch?v=9wfZH6ZWxmk&
46
$

Disruptive technologies

1. Mobile Internet
2. Automation of knowledge work
3. The internet of things
4. Cloud technology
5. Advance robotics
6. (near) Autonomous vehicles

7. Next-generation genomics
8. Energy storage
9. 3D printing
10. Advance materials
11. Advanced oil & gas exploration
12. Renewable energy

http://www.mckinsey.com/insights/business_technology/disruptive_technologies
47
$

#2 in disruptive technologies list

Automation of knowledge work!

$5-7 trillion
Potential economic impact by 2025
48
$

The ‗Internet of Everything‘

http://news.cnet.com/8301-1001_3-57589613-92/whats-the-internet-of-everything-worth-$613-billion-cisco-reckons
49
$

The ‗Internet of Everything‘

http://www.cisco.com/web/about/ac79/innov/IoE.html
50
$

‗Internet of Everything‘: $14.4T in 10 years

http://www.cisco.com/web/about/ac79/innov/IoE.html
51
$

Big data & big hype!

52
$

Data crunching tool, long long ago

Abacus

53
$

Data crunching tools over time

Abacus

Slide rule

Calc.

Excel

Today: more and rapidly improving tools.
54
$

Rapidly improving field

chart
already outdated!
55
$

Tools: depends on what you do with it

56
$

Right tool for the right job!

57
$

Opportunities, tools & people

Opportunities

Tools

People (talent)

58
$

Shortage of talent
http://fcw.com/Articles/2012/10/29/big-data-skillset-gaps.aspx

http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
59
$

Shortage of talent

―By 2018, the US alone could face a shortage of:
140,000 to 190,000 people with deep analytical skills,
1.5 million managers & analysts with the know-how to
use the analysis of big data to make effective decisions.‖

http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
60
$

Low supply, high demand:

Relatively high compensation.
http://www.forbes.com/sites/gilpress/2013/06/03/data-science-news-roundup-becoming-a-profession-at-300hour
61
$

New job category

―Bureau of Labor Statistics, which lists salary trends and forecasts job growth for
many different positions, doesn‘t even have a category for data scientists.‖ !

―Equivalent of few persons
in one position‖

http://finance.yahoo.com/blogs/big-data-download/hottest-job-21st-century-bet-151026538.html
62
$

Opportunities with data science

ashiqur@gmail.com

ashiqur@gmail.com

@ashiq

linkedin.com/in/ashiq
63

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Opportunities with data science

  • 1. $ Opportunities with Data Science Ashiq Rahman, Ph.D. Principal Strategy Planner, Fujitsu Network Communications ashiqur@gmail.com Tableau User Group, Dallas. October 29, 2013
  • 3. $ About me: problem solver with technology Ph.D, 1999 Quantum Optics Early Big Data Architected & built simulation platform Startup within big company B.Sc. (4.0 GPA) Math & Physics High school, 1988 2nd rank, nationwide Statistical modeling Wireless systems System engineering Network architecture Strategy Planning Network graphs 100G Business development Data science 2
  • 4. $ About me: always learning 3
  • 5. $ About me: Organize & DJ Tango events 4
  • 6. $ About me: Host of Tango in Klyde Warren Park http://www.facebook.com/tangointheparkdallas 5
  • 12. $ Data driven decision making Data not available on time Decisions are delayed Data not available/no access Decisions are made with assumptions & ‗gut feel‘. 11
  • 13. $ Relying only on gut feel can backfire! 12
  • 14. $ Empowerment of decision makers Data not accessible in an easy manner. Limited trends/patterns analysis (‗food for thought‘ for innovation). Innovation Not enough scorecards, KPIs … 13
  • 16. $ Vision – Decision Support System ―The system is not just about displaying reports, but rather must be a platform for decision making in the broadest sense‖ - Ralph Kimball, one of the original architects of Data Warehousing. 15
  • 17. $ Inspiration Zoom & Layer feature in Google maps 16
  • 19. $ Tips – server look customization Customization supported by Tableau http://onlinehelp.tableausoftware.com/current/server/en-us/help.htm#customize_namelogo.htm 18
  • 20. $ Tips – server look customization Unsupported Hack! C:Program Files (x86)TableauTableau Server8.0wgserverpublic Replace this (Back it up) With this favicon.ico should be 32x32 pixels Go to: <ServerURL>/favicon.ico Refresh in the browser 19
  • 23. $ Tips – information layering 22
  • 24. $ Relation & network graphs Multiple platforms 23
  • 25. $ Knowledge & wisdom ! ‗Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?‘ T.S. Eliot, ―Choruses from The Rock‖ (1934) ―Knowledge is knowing that a tomato is a fruit; wisdom is knowing not to put it in a fruit salad.‖ Brian O'Driscoll (2009) from Miles Kington 24
  • 26. $ Visual analytics to wisdom ! Past Sales Bookings Forecast What is happening now? What will happen? Reports Insight Future What happened? Data Present Alerts How & why did it happen? What’s the next best action? Prediction What’s the best/worst case? 25
  • 27. $ DSS: User experiences excitements! ―This is an awesome and valuable tool.‖ - Marketing ―It is extremely easy to navigate.‖ - Accounting ―It is like treasure hunt.‖ - Sales ―Haven‘t seen anything like this in my whole life !‖ - Planning 26
  • 28. $ Recommendation from strategy leaders ―You got to make a decision support tool that the frontline users understands.‖ ―The moment you make it simple & understandable, then people start using it and you get better decisions.‖ http://www.mckinsey.com/features/advanced_analytics 27
  • 29. $ Analytics to $: Lead of analytical team Internal data analytics Increased sales Andrew Pole ―Between 2002 — when Pole was hired — and 2010, Target‘s revenues grew from $44 billion to $67 billion.‖ http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did 28
  • 30. $ Analytics to $: How much is a mortgage contract worth? (mid 1990) Public data External valuation Dan Steinberg Internal data & analytics Better valuation Hold or Sell ? Additional $600* million in profit during the first year alone! *($800 million today). http://www.linkedin.com/groups/Chase-Banks-Big-Win-Predicting-1005097.S.177355288 29
  • 31. $ Visualization to ―control of spreadsheets‖ JPMorgan lost more than $6B in 2012 due to ―deficiencies found in the internal control environment, ... and lack of control over spreadsheets ..‖ http://en.wikipedia.org/wiki/JPMorgan_Chase 30
  • 32. $ ‗Big data, analytics & the path from insights to value‘ ―Top performers say Analytics is a key differentiator‖ ―Organizations expect that the ability to visualize data differently will be the most valuable technique‖ http://sloanreview.mit.edu/article/big-data-analytics-and-the-path-from-insights-to-value/ 31
  • 33. $ Analytics trumps intuition Top performing companies use analytics more than intuition. A likelihood of 1.0 indicated an equal likelihood that the organizations will use either analytic or intuition. 32
  • 34. $ Where analytic work done Analytics migrate toward more centralized units, first at the local line of business and then at the enterprise level. 33
  • 35. $ What it takes: Information visualization 34
  • 36. $ What it takes: Aesthetics & design http://www.ideo.com 35
  • 37. $ What it takes: expertise in many areas Business, process, technology Finance, accounting High level analytics & platforms Vision ―Data Science‖ IT Hacking! Develop Design & aesthetics Deliver Information visualization Problem solver Agile, curious Human psychology (story telling, …) 36
  • 38. $ What it takes: Data science http://en.wikipedia.org/wiki/Data_science 37
  • 39. $ Imagine in future … It‘s not science fiction anymore! Inspiration movie: ―Minority report (2002)‖ 38
  • 40. $ Science fiction, not anymore ! 39
  • 41. $ 2012 Election results prediction #NateSilverFacts • If you liked Chuck Norris facts, you'll love Nate Silver facts! • When Nate Silver asks you "Wanna make a bet?" The correct answer is no. • Nate Silver doesn't "crunch" numbers. Numbers disintegrate in fear before him. • Outliers exist because they're hiding from Nate Silver. 40
  • 43. $ Self-driving car: ―Look Ma, no hands!‖ 42
  • 44. $ Self-driving car: pattern recognition & action Similar technology can be used in many areas. 43
  • 45. $ IBM Watson competes Jeopardy & wins! 44
  • 46. $ IBM Watson as doctor‘s aid Utilization management decisions in lung cancer treatment. 90% of nurses in the field who use Watson now follow its guidance. 45
  • 48. $ Disruptive technologies 1. Mobile Internet 2. Automation of knowledge work 3. The internet of things 4. Cloud technology 5. Advance robotics 6. (near) Autonomous vehicles 7. Next-generation genomics 8. Energy storage 9. 3D printing 10. Advance materials 11. Advanced oil & gas exploration 12. Renewable energy http://www.mckinsey.com/insights/business_technology/disruptive_technologies 47
  • 49. $ #2 in disruptive technologies list Automation of knowledge work! $5-7 trillion Potential economic impact by 2025 48
  • 50. $ The ‗Internet of Everything‘ http://news.cnet.com/8301-1001_3-57589613-92/whats-the-internet-of-everything-worth-$613-billion-cisco-reckons 49
  • 51. $ The ‗Internet of Everything‘ http://www.cisco.com/web/about/ac79/innov/IoE.html 50
  • 52. $ ‗Internet of Everything‘: $14.4T in 10 years http://www.cisco.com/web/about/ac79/innov/IoE.html 51
  • 53. $ Big data & big hype! 52
  • 54. $ Data crunching tool, long long ago Abacus 53
  • 55. $ Data crunching tools over time Abacus Slide rule Calc. Excel Today: more and rapidly improving tools. 54
  • 57. $ Tools: depends on what you do with it 56
  • 58. $ Right tool for the right job! 57
  • 59. $ Opportunities, tools & people Opportunities Tools People (talent) 58
  • 61. $ Shortage of talent ―By 2018, the US alone could face a shortage of: 140,000 to 190,000 people with deep analytical skills, 1.5 million managers & analysts with the know-how to use the analysis of big data to make effective decisions.‖ http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation 60
  • 62. $ Low supply, high demand: Relatively high compensation. http://www.forbes.com/sites/gilpress/2013/06/03/data-science-news-roundup-becoming-a-profession-at-300hour 61
  • 63. $ New job category ―Bureau of Labor Statistics, which lists salary trends and forecasts job growth for many different positions, doesn‘t even have a category for data scientists.‖ ! ―Equivalent of few persons in one position‖ http://finance.yahoo.com/blogs/big-data-download/hottest-job-21st-century-bet-151026538.html 62
  • 64. $ Opportunities with data science ashiqur@gmail.com ashiqur@gmail.com @ashiq linkedin.com/in/ashiq 63