Data Visualization and Storytelling

1. DATA VISUALIZATION
IT’S ALL RELATIVE
Tamarah Usher
May 02 2017

2. 2
DATA
STORY VISUAL
*

3. 3
“Before we were born, a whole society of storytellers
was already here. The storytellers who were here
before us, taught us how to be human.”
- Miguel Angel Ruiz
“Before we were born, a whole society of storytellers
was already here. The storytellers who were here
before us, taught us how to be human.”
- Miguel Angel Ruiz

4. 4
A narrative (or story) is any account of
connected events, presented to a reader or
listener in a sequence of written or spoken
Words or pictures
NARRATIVE ARC
TENSION
TIME

5. 5
THE SCIENCE OF STORYTELLING
Arthur Quiller-Couch (1924)
• Man vs Man
• Man vs Nature
• Man vs God
• Man vs Society
• Man in the Middle
• Man and Woman
• Man vs Himself
SEVEN BASIC CONFLICTS
Christopher Booker (2004)
• Comedy
• Tragedy
• Rebirth
• The Quest
• Rags to Riches
• Voyage and Return
• Overcoming the Monster
SEVEN BASIC PLOTS
Aristotle (335 BC)
• Mythos (plot)
• Ethos (character)
• Dianoia (thought)
• Lexis (diction)
• Melos (melody)
• Opsis (spectacle)
TRAGEDY

6. 6
"I can take any empty space and call it a
bare stage. A man walks across this
empty space whilst someone else is
watching him, and this is all that is
needed for an act of theatre to be
engaged.”
- Peter Brook, The Empty Space

7. 7
DATA
STORY VISUAL
*

8. 8

9. 9
GESTALT PRINCIPLES OF PERCEPTION
Proximity: Objects that are close together or
connected are perceived as a group
Similarity: Objects that share similar attributes,
color or shape are perceived as a group
Enclosed and Continuity: Objects that appear to
have a boundary or continuation around them
are perceived as a group
Closure: Open structures can be easily
perceived as closed, complete

10. 10
DATA
STORY VISUAL
*

11. 11
A PICTURE IS WORTH 1000 WORDS

12. 12
HISTORY OF COMMUNICATION

13. 13
FLORENCE NIGHTINGALE, WAR DEATHS (1855)

14. 14
JOHN SNOW, LONDON CHOLERA MAP (1854)

15. 15
DATA
STORY VISUAL
*

16. 16
DATA IS
EVERYWHERE
AFFILIATES
TIME
DEVICE
DISPLAY
ADS
EMAIL
CRM DATA
SOCIAL
WEATHER
SEARCH
COOKIE DATA
CUSTOMER
PREFERENCES
LOCATION

17. 17
ITS GETTING BIGGER

18. 18
FIND THE RELATIONSHIP
NOMINAL COMPARISON
This is a simple comparison of the
quantitative values of subcategories.
Example: Number of visitors to various
websites.
TIME SERIES
This tracks changes in values of consistent
metrics over time. Example: Monthly sales
CORRELATION
This is data with two or more variables that
may demonstrate positive or negative
correlation to each other. Example:
Salaries according to education level.
RANKING
This shows how two or more values
compare to each other in relative
magnitude. Example: Historic weather
patterns, ranked from the hottest months to
the coldest.
DEVIATION
This examines how data points relate
to each other, particularly how far any
given data point differs from the
mean. Example: Amusement park
tickets sold on a rainy day vs regular
day.
PART-TO-WHOLE RELATIONSHIPS
This shows a subset of data
compared to the larger whole.
Example: Percentage if customers
purchasing specific products.
DISTRIBUTION
This shows data distribution, often
around a central value. Example:
Heights of players on a basketball
team.

19. 19
ASK A QUESTION
FLOWCHART
Relationship,
Hierarchy
COMPARISON
Comparative
Representation
MAP
Position in Space
PORTRAIT
Distribution
Representation
MULTIVARIABLE
Deduction & Prediction
TIMELINE
Position in Time

20. 20
DATA
STORY VISUAL
* GRAPHGRAPH

21. 21
“The greatest value of a picture is
when it forces us to notice what we
never expected to see”
- John Tukey, 1977

22. 22
HOW MANY 5’S CAN YOU FIND?
142536789251364789245369178
419356728495126783149356728
245369178145672893145672938
495126783149356728423698517
359164782145672938451672938
465132978423698517459163782
145762938451672938359164782
431567298459163782431567298

23. 23
PROXIMITY
142 5 367892 5 136478924 5 369178
4193 5 672849 5 1267831493 5 6728
24 5 36917814 5 67289314 5 672938
49 5 1267831493 5 6728423698 5 17
3 5 916478214 5 6729384 5 1672938
46 5 132978423698 5 174 5 9163782
14 5 7629384 5 16729383 5 9164782
431 5 672984 5 9163782431 5 67298

24. 24
ALIGNMENT
555 142367892136478924369178
555 419367284912678314936728
555 243691781467289314672938
555 491267831493672842369817
555 391647821467293841672938
555 461329784236981749163782
555 147629384167293839164782
555 431672984916378243167298

25. 25
REPITITION
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789
123456789 123456789 123456789

26. 26
CONTRAST
142536789251364789245369178
419356728495126783149356728
245369178145672893145672938
495126783149356728423698517
359164782145672938451672938
465132978423698517459163782
145762938451672938359164782
431567298459163782431567298

27. 27
SUBTRACTION
142536789251364789245369178
419356728495126783149356728
245369178145672893145672938
495126783149356728423698517
359164782145672938451672938
465329784236981517459163782
145762938451672938359164782
431567298459163782431567298

28. 28
ANSCOMBE’S QUARTET – DATA SETS
I II III IV
x y x y x y x y
10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71
9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84
11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47
14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04
6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25
4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50
12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56
7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89

29. 29
ANSCOMBE’S QUARTET - STATISTICS
Property Value Accuracy
Mean of x 9 exact
Sample variance of x 11 exact
Mean of y 7.50 to 2 decimal places
Sample variance of y 4.125 plus/minus 0.003
Correlation between x and y 0.816 to 3 decimal places
Linear regression line y = 3.00 + 0.500x
to 2 and 3 decimal places,
respectively

30. 30
ANSCOMBE’S QUARTET - GRAPHED

31. 31
DATA
STORY VISUAL
* GRAPH

32. 32
ELEMETS OF A DATA DRIVEN STORY
LITERATURE
Characters
Vladimir, Lucky, Buffy
Time
Evening, 1853
Settings
A country road, Europe, Space
Plot
Man vs Man, Man vs Himself
DATA VISUALIZATION
Metrics
Logistics Spending
Time
Fiscal Year 2017
Settings
Cost to Serve, Miles Driven
Plot
What is the trend for Logistics
spend?

33. 33
STORYTELLING IN BUSINESS
PEOPLE NEED TO MAKE DECISIONS, SO GIVE THEM A SIGN
The most common focus for storytelling in
business is to persuade, influence and motivate
an audience.
RISK
REWARD

34. 34
FOLLOW THE PROCESS
DATA
EXPORT
CHART
SLIDES
PRESENT
DECIDE

35. 35
NARRATIVE CONSTRUCTION
1) IDEAL 2) REALITY 3) PROBLEM 4) SOLUTION 5) NEXT STEP

36. 36
DATA STORYTELLING BEST PRACTICES
CONNECT WITH PEOPLE
KEEP IT SIMPLE
TRY TO CONVEY ONE IDEA
EXPLORE THE THINGS YOU
KNOW BEST

37. 37

38. 38
THANK YOU TAMARAH USHER