Successfully convince people with data visualization video of presentation available at https://www.youtube.com/watch?v=3PKjNnt14mk from Data by the Bay conference

1. Midnight
January 28, 1986
Lives are on the line
Importance of rethinking data visualization
Successfully Convince People with Data
http://kylehailey.com
Kylelf@gmail.com

3. The journey of simplicity
1. Seems simple
“When you start looking at a problem and it seems really simple, you don’t
really understand the complexity of the problem.” – Steve Jobs
Designing an Interface

4. The journey of simplicity
1. Seems simple
“When you start looking at a problem and it seems really simple, you don’t
really understand the complexity of the problem.” – Steve Jobs
2. Realize it’s complex

5. The journey of simplicity
1. Seems simple
“When you start looking at a problem and it seems really simple, you don’t
really understand the complexity of the problem.” – Steve Jobs
2. Realize it’s complex
3. Create complex solution
“Then you get into the problem, and you see that it’s really complicated,
and you come up with all these convoluted solutions. That’s sort of the
middle, and that’s where most people stop.” – Steve Jobs

6. The journey of simplicity
1. Seems simple
“When you start looking at a problem and it seems really simple, you don’t
really understand the complexity of the problem.” – Steve Jobs
2. Realize it’s complex
3. Create complex solution
“Then you get into the problem, and you see that it’s really complicated,
and you come up with all these convoluted solutions. That’s sort of the
middle, and that’s where most people stop.” – Steve Jobs
4. Complex solution is bad

7. The journey of simplicity
1. Seems simple
“When you start looking at a problem and it seems really simple, you don’t
really understand the complexity of the problem.” – Steve Jobs
2. Realize it’s complex
3. Create complex solution
“Then you get into the problem, and you see that it’s really complicated,
and you come up with all these convoluted solutions. That’s sort of the
middle, and that’s where most people stop.” – Steve Jobs
4. Complex solution is bad
5. Simple powerful is hard
“But the really great person will keep on going and find the key, the
underlying principle of the problem — and come up with an elegant, really
beautiful solution that works.” – Steve Jobs

9. Prototype & Iterate

10. Example Problem
How so you analyze performance of a system?

11. What is a day in the life lookWhat is a day in the life look
like for a DBA who haslike for a DBA who has
performance issues?performance issues?
Example: performance data

12. Linux performance tools

13. Midnight
January 28, 1986
Lives are on the line
Thanks to Edward Tufte
Night before the Flight
Jan 27,1986

14. Estimated launch
temperature 29º

15. 13 Pages Faxed

16. 13 Pages Faxed
3 different types of names

17. Damage (in overwhelming detail)
but No Temperatures
13 Pages Faxed

18. 13 Pages Faxed
Missing Data for 5 erosion
damage flights
Blow by Damage
Test engines fired horizontally

19. 13 Pages Faxed
Shows “blow by”, not more important “erosion”
Damage at hottest
and coldest launches
* (of the flights shown)
Next day’s flight

20. 13 Pages Faxed
Predict
Temperature
Recommendation

21. 55 65 7560 70 80
1
Original Engineering data
2
3
““damages atdamages at
the hottestthe hottest
and coldestand coldest
Temperature”Temperature”
Would you launch?

23. Congressional Hearings
Evidence
No Damage Legend
Damage hard to read

24. Congressional Hearings
Evidence
Temperature
correlation difficult

25. 55 65 7560 70 80
1
Original Data
2
3

26. Clearer
1. Y-Axis amount of damage (not number of damage)
55 65 7560 70 80
4
8
12

27. 1. Y-Axis amount of damage (not number of damage)
2. Include successes *
55 65 7560 70 80
4
8
12
Clearer
* Only external temperatures were known not the
temperature of the solid rocket boosters
Be accurate enough

28. 1. Y-Axis amount of damage (not number of damage)
2. Include successes
3. Mark Differences
55 65 7560 70 80
4
8
12
Clearer

29. 1. Y-Axis amount of damage (not number of damage)
2. Include successes
3. Mark Differences
4. Normalize same temp
55 65 7560 70 80
4
8
12
Clearer

30. 1. Y-Axis amount of damage (not number of damage)
2. Include successes
3. Mark Differences
4. Normalize same temp
55 65 7560 70 80
4
8
12
Clearer
Damage on
every flight
below 65
No damage on
every flight
above 75

31. 1. Y-Axis amount of damage (not number of damage)
2. Include successes
3. Mark Differences
4. Normalize same temp
55 65 7560 70 80
4
8
12
Clearer
Known
World

32. 1. Y-Axis amount of damage (not number of damage)
2. Include successes
3. Mark Differences
4. Normalize same temp
5. Scale known vs unknown
55 65 7560 70 80
4
8
12
4
8
12
30 40 5035 45
XX
Clearer

33. Difficult
 NASA Engineers Fail
 Congressional Investigators Fail
 Data Visualization is Difficult
But …
Lack of Clarity can be devastating

34. Visualization can be
powerful

35. “If I can't picture it, I can't understand it”
Anscombe's Quartet
I II III IV
x y x y x y x y
10 8.04 10 9.14 10 7.46 8 6.58
8 6.95 8 8.14 8 6.77 8 5.76
13 7.58 13 8.74 13 12.74 8 7.71
9 8.81 9 8.77 9 7.11 8 8.84
11 8.33 11 9.26 11 7.81 8 8.47
14 9.96 14 8.1 14 8.84 8 7.04
6 7.24 6 6.13 6 6.08 8 5.25
4 4.26 4 3.1 4 5.39 19 12.5
12 10.84 12 9.13 12 8.15 8 5.56
7 4.82 7 7.26 7 6.42 8 7.91
5 5.68 5 4.74 5 5.73 8 6.89
Average 9 7.5 9 7.5 9 7.5 9 7.5
Standard Deviation 3.31 2.03 3.31 2.03 3.31 2.03 3.31 2.03
Linear Regression 1.33 1.33 1.33 1.33
- Albert Einstein- Albert Einstein

36. Graphics for Anscombe’s Quartet

37. Counties in US
 > 3000 Counties
 > 50 pages
“The humans … are exceptionally
good at parsing visual information.”
Knowledge representation in cognitive science. Westbury, C. & Wilensky, U. (1998)

38. Visualizations can also obfuscate

39. Pretty Picture

40. Spaghetti at the wall

41. Spaghetti at the wall II

42. Amazon Cloudwatch

43. Imagine Trying to Drive your
Car
And is updated once and hourAnd is updated once and hour
Or would you like it toOr would you like it to
look …look …
Would you want your dashboard to look like :Would you want your dashboard to look like :

44. If you are not tuning for time, you are wasting time
Max CPU
(yard stick)
Top ActivityTop Activity
SQLSQL
SessionsSessions
LOADLOAD

45. Looking at many targets

46. When Developers sayWhen Developers say
The Database is slowThe Database is slow

49. AAS ~= 0AAS ~= 0

50. Do You Want?
Engineering Data?Engineering Data?

51. Pretty PicturesPretty Pictures
Do You Want?

52. Clean and ClearClean and Clear
? ? ? ?? ? ? ?
? ?? ?
Do You Want?

53. Summary
• Textual statistics – difficult to parse
• Pretty pictures misleading
• Goal clear graphics powerful
Graphics add power and clarity
to quantitative data
but there needs to be domain understanding
Kylelf@gmail.com
http://kylehailey.com