Successfully convince people with data visualization

Midnight January 28, 1986 Lives are on the line

Importance of rethinking data visualization Successfully Convince People with Data

http://kylehailey.comKylelf@gmail.com

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

The journey of simplicity1. 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

The journey of simplicity1. 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

The journey of simplicity1. 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

The journey of simplicity1. 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 bad5. 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

Prototype & Iterate

Example Problem

How so you analyze performance of a system?

What is a day in the life look What is a day in the life look like for a DBA who has like for a DBA who has performance issues?performance issues?

Example: performance data

Linux performance tools

Midnight January 28, 1986 Lives are on the line

Thanks to Edward Tufte

Night before the Flight

Jan 27,1986

Estimated launch temperature 29º

13 Pages Faxed

13 Pages Faxed

3 different types of names

Damage (in overwhelming detail) but No Temperatures

13 Pages Faxed

13 Pages Faxed

Missing Data for 5 erosion damage flights

Blow by Damage

Test engines fired horizontally

13 Pages Faxed

Shows “blow by”, not more important “erosion”

Damage at hottest and coldest launches* (of the flights shown)

Next day’s flight

13 Pages Faxed

Predict Temperature

Recommendation

55 65 7560 70 80

1

Original Engineering data

2

3

““damages atdamages atthe hottest the hottest and coldest and coldest Temperature” Temperature”

Would you launch?

Congressional Hearings Evidence

No Damage LegendDamage hard to read

Congressional Hearings Evidence

Temperature correlation difficult

55 65 7560 70 80

1

Original Data

2

3

Clearer

1. Y-Axis amount of damage (not number of damage)55 65 7560 70 80

4

8

12

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

1. Y-Axis amount of damage (not number of damage)2. Include successes3. Mark Differences

55 65 7560 70 80

4

8

12

Clearer

1. Y-Axis amount of damage (not number of damage)2. Include successes3. Mark Differences4. Normalize same temp

55 65 7560 70 80

4

8

12

Clearer

1. Y-Axis amount of damage (not number of damage)2. Include successes3. Mark Differences4. 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

1. Y-Axis amount of damage (not number of damage)2. Include successes3. Mark Differences4. Normalize same temp

55 65 7560 70 80

4

8

12

Clearer

Known World

1. Y-Axis amount of damage (not number of damage)2. Include successes3. Mark Differences4. Normalize same temp5. Scale known vs unknown

55 65 7560 70 80

4

8

12

4

8

12

30 40 5035 45

XX

Clearer

Difficult

NASA Engineers Fail Congressional Investigators Fail Data Visualization is Difficult

But …

Lack of Clarity can be devastating

Visualization can be powerful

“If I can't picture it, I can't understand it”

Anscombe's QuartetI II III IV

x y x y x y x y10 8.04 10 9.14 10 7.46 8 6.588 6.95 8 8.14 8 6.77 8 5.76

13 7.58 13 8.74 13 12.74 8 7.719 8.81 9 8.77 9 7.11 8 8.84

11 8.33 11 9.26 11 7.81 8 8.4714 9.96 14 8.1 14 8.84 8 7.046 7.24 6 6.13 6 6.08 8 5.254 4.26 4 3.1 4 5.39 19 12.5

12 10.84 12 9.13 12 8.15 8 5.567 4.82 7 7.26 7 6.42 8 7.915 5.68 5 4.74 5 5.73 8 6.89

Average 9 7.5 9 7.5 9 7.5 9 7.5Standard Deviation 3.31 2.03 3.31 2.03 3.31 2.03 3.31 2.03Linear Regression 1.33 1.33 1.33 1.33

- Albert Einstein- Albert Einstein

Graphics for Anscombe’s Quartet

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)

Visualizations can also obfuscate

Pretty Picture

Spaghetti at the wall

Spaghetti at the wall II

Amazon Cloudwatch

Imagine Trying to Drive your Car

And is updated once and hourAnd is updated once and hour

Or would you like it to Or would you like it to look …look …

Would you want your dashboard to look like :Would you want your dashboard to look like :

If you are not tuning for time, you are wasting time

Max CPU

(yard stick)

Top Activity Top Activity

SQLSQLSessionsSessions

LOADLOAD

Looking at many targets

When Developers say When Developers say

The Database is slowThe Database is slow

AAS ~= 0AAS ~= 0

Do You Want?

Engineering Data?Engineering Data?

Pretty PicturesPretty Pictures

Do You Want?

Clean and Clear Clean and Clear

? ? ? ? ? ? ? ? ? ?? ?

Do You Want?

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.comhttp://kylehailey.com