Presented live via teleconference on June 13, 2019

1. Madison Tableau User Group
Introducing the WISDOM Data-Working Flow

2. © 2018 Data Literacy. All rights reserved. 2

3. © 2018 Data Literacy. All rights reserved. 3
The 6 Sigma DMAIC Methodology

4. © 2018 Data Literacy. All rights reserved. 4
The DEMING PDCA Cycle
W. Edwards Deming
“The PDCA cycle…can
be traced back to S.
Mizuno of the Tokyo
Institute of Technology in
1959
Used in business for the
control and continuous
improvement of
processes and products.”
https://en.wikipedia.org/wiki/PDCA

5. © 2018 Data Literacy. All rights reserved. 5
CRISP-DM
Cross-industry standard process for data mining
“Conceived in 1996 and
became a European Union
project under
the ESPRIT funding
initiative in 1997.
The first version of the
methodology was
presented at the 4th
CRISP-DM SIG Workshop
in Brussels in March 1999”
https://en.wikipedia.org/wiki/Cross-industry_standard_process_for_data_mining

6. © 2018 Data Literacy. All rights reserved. 6
The Scientific Method

7. © 2018 Data Literacy. All rights reserved. 7

8. Introducing the WISDOM Data Working
Flow

9. © 2018 Data Literacy. All rights reserved. 9
Climbing the Staircase of WISDOM

10. © 2018 Data Literacy. All rights reserved. 10

11. © 2018 Data Literacy. All rights reserved. 11
A Continuous Journey to a Higher Place

12. © 2018 Data Literacy. All rights reserved. 12
Each Step on the Stairway involves Flow
START
PROCESS
DEC-
ISION
DATA
PREPARE
DOCUMENT
SHAPE KEY

13. © 2018 Data Literacy. All rights reserved. 13

14. Make an
observation
WONDER
Research is formalized curiosity.
It is poking and prying with a
purpose. It is a seeking that he who
wishes may know the cosmic secrets
of the world and they that dwell
therein.”
ZORA NEALE
HURSTON
Author of African American
literature, Anthropologist

15. © 2018 Data Literacy. All rights reserved. 15
A quick mental task
Assuming aces are
worth 11, quickly
double the value of
each card below and
add them up.
https://www.psychologytoday.com/us/blog/mind-games/201307/inattentional-blindness-and-video-games

16. © 2018 Data Literacy. All rights reserved. 16
A quick mental task
The answer is 50, but did
you notice something
wrong with the picture?
If you look again, now
do you see it?
https://www.psychologytoday.com/us/blog/mind-games/201307/inattentional-blindness-and-video-games

17. © 2018 Data Literacy. All rights reserved. 17
Four Tips for Observing Well
Keep an
Observations
and Ideas
Journal
Slow down,
breathe, be
mindful of
your
surroundings
Minimize
distractions
and focus on
one task
Be aware of
cognitive
biases and
fallacies

18. Make an
observation
Ask a worthwhile
question
WONDER

19. Make an
observation
Ask a worthwhile
question
WONDER
The 6 Forms of Questions

20. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
WONDER
For example, the claim "all swans are white" is
falsifiable since it is contradicted by this basic
statement: "In 1697, during the Dutch explorer Willem
de Vlamingh expedition, there were black swans on
the shore of the Swan River in Australia", which in
this case is a true observation.
Sir Karl Popper stated that “statements or systems of
statements, in order to be ranked as scientific, must
be capable of conflicting with possible, or conceivable
observations”.
So falsifiability became his criterion of demarcation
between statements and theories of science and
those of religion, pseudoscience, and all other forms.
SIR KARL POPPER
Philosopher of Science

21. Quiz: Which statements below aren’t falsifiable?
A. “It will rain tomorrow.”
B. “It rains every day, everywhere.”
C. “It will rain someday.”
D. “It is what it is.”

22. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
WONDER
N
Find & gather
data or create it
yourself

23. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
1642, Abel
Tasman
Zeehaen’s Bight
1769, James Cook
complete circumnavigation
Cook’s Strait

24. In 1642, Abel Tasman was the first
European to discover New
Zealand. He mistakenly though
the two islands were connected,
and named the area between the
Zeehaen’s Bight, after his ship

25. In 1769, over a century later,
James Cook was the first
European to completely
circumnavigate the pair of
islands that make up the native
home of the Māori people. He
correctly noticed that there
was a navigable passage
through, and the two land
masses weren’t connected. The
area between them is now
knows as Cook Strait

26. 10 Questions to Help You
Explore the Contours of Your Data
1. GRANULARITY: What does a single record mean?
2. ROWS: How many total records are there?
3. COLUMNS: How many different variables are there?
4. TYPES: Are variables nominal, ordinal, interval or
ratio?
5. UNIQUE KEY: Is one of the variables unique?
6. BOUNDARIES: What are the min & max of the
quantitative variables?
7. SHAPE: What are the distributions of the quantitative
variables?
8. LEVELS: What are the values of the qualitative
variables?
9. HIERARCHIES: Do some levels form hierarchies?

27. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Explore its contours
and shape
WONDER SEEK
N
input
Find & gather
data or create it
yourself
Find another question
Intuition will tell
the thinking mind
where to look next.”
JONAS SALK
Medical researcher and
virologist. Developer of one of
the 1st polio vaccines.
Y

28. Intuition – n
The ability to
understand something
immediately, without
the need for conscious
reasoning
From Latin intuērī –
to look at, to
gaze upon

29. © 2018 Data Literacy. All rights reserved. 29
A Knee-Jerk Reaction to a False Dichotomy

30. If data is the new oil….
…then intuition is the spark
plug.

31. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
Did you
answer
your
question?
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?
Get more data, fix
issues, and/or re-
analyze
Enact any
appropriate changes
or decisions
WONDER SEEK DISCOVER MATURE
Y
N N
Y Y
N
Y
N
Clean and
structure it
for analysis
Craft & deliver a
notable message
input output
Find & gather
data or create it
yourself
Find another question
START
PROCESS
DEC-
ISION
DATA
PREPARE
DOCUMENT
SHAPE KEY
N
Analyze it to see what
it’s saying & not saying
Determine both the
practical & the
statistical significance
Explore its contours
and shape
Analyze it to see what
it’s saying & not saying
Did you
answer
your
question?
Do new
questions
arise that
change
things?
Enact any
appropriate changes
or decisions
Craft & deliver a
notable message
Make an
observation

32. © 2018 Data Literacy. All rights reserved. 32
Knowing why any of it matters in the first place
Knowing what the data is telling us & not telling us
Knowing where to look next
Knowing when to stop looking and take action
Knowing who needs to hear & how to get through to the
1
2
3
4
5
The 5 Roles of Human Intuition in Analytics

33. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Find another question

34. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Find another question
Clean and
structure it
for analysis
N

35. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Find another question
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y

36. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question

37. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?

38. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N

39. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N

40. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N
Y
Craft & deliver a
notable message
MATURE
output

41. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N
Y
Craft & deliver a
notable message
MATURE
output
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?

42. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N
Y
Craft & deliver a
notable message
MATURE
output
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?
Y

43. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Get more data, fix
issues, and/or re-
analyze
N
Y
Craft & deliver a
notable message
MATURE
output
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?
Y
Enact any
appropriate changes
or decisions
N

44. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
Analyze it to see what
it’s saying & not saying
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?
Get more data, fix
issues, and/or re-
analyze
Enact any
appropriate changes
or decisions
WONDER SEEK DISCOVER MATURE
Y
N N
Y Y
N
Y
N
Clean and
structure it
for analysis
Craft & deliver a
notable message
input output
Find & gather
data or create it
yourself
Find another question
START
PROCESS
DEC-
ISION
DATA
PREPARE
DOCUMENT
SHAPE KEY

46. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
WONDER
Observation: I’ve noticed people
suffering from brain cancer a lot
recently. These people live in the United
States
Question: I wonder how the US
compares with other countries in terms
of brain cancer incidence rate….
Hypothesis: I bet the United States is
in the top 10 in recent years in terms of
brain cancer incidence rate when
compared with other countries.

47. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
WONDER
N
Find & gather
data or create it
yourself
http://ghdx.healthdata.org/gbd-results-tool

49. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself

51. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question

55. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
Analyze it to see what
it’s saying & not saying
DISCOVER
N
Y
Find another question

57. http://hdr.undp.org/en/data#

59. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
WONDER SEEK
Y
N
input
Find & gather
data or create it
yourself
Clean and
structure it
for analysis
DISCOVER
N
Find another question

61. © 2018 Data Literacy. All rights reserved. 61
What’s in a name?
“American
Samoa”
“Macedonia”
“Taiwan”
“Samoa”
”The Former
Yugoslav Republic
of Macedonia”
---

62. © 2018 Data Literacy. All rights reserved. 62
More schooling correlated with higher incidence rate

63. © 2018 Data Literacy. All rights reserved. 63
Adding the trendline

65. © 2018 Data Literacy. All rights reserved. 65
Sizing by Population

66. © 2018 Data Literacy. All rights reserved. 66
Adding Clustering

67. Make an
observation
Ask a worthwhile
question
Form a falsifiable
hypothesis
Do you
have
relevant
data?
Consider its potential
shortcomings
Is it ready
for
analysis?
Explore its contours
and shape
Analyze it to see what
it’s saying & not saying
Determine both the
practical & the
statistical significance
Did you
answer
your
question?
Listen to your
audience’s feedback
Do new
questions
arise that
change
things?
Get more data, fix
issues, and/or re-
analyze
Enact any
appropriate changes
or decisions
WONDER SEEK DISCOVER MATURE
Y
N N
Y Y
N
Y
N
Clean and
structure it
for analysis
Craft & deliver a
notable message
input output
Find & gather
data or create it
yourself
Find another question

68. © 2018 Data Literacy. All rights reserved. 68
Thank You!
Q&A