Successfully convince people with data visualization
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The document discusses the complexities of data visualization, emphasizing the importance of simplicity and clarity in presenting performance metrics. It critiques the tendency to create complicated solutions instead of finding elegant, simple answers, using examples such as NASA's Challenger disaster to illustrate the consequences of inadequate data visualization. The author advocates for clear graphics to enhance understanding and decision-making in engineering contexts.
Successfully convince people with data visualization
- 1. Midnight January 28, 1986 Lives are on the line Importance of rethinking data visualization Successfully Convince People with Data http://kylehailey.com [email protected]
- 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
- 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
- 13. Midnight January 28, 1986 Lives are on the line Thanks to Edward Tufte Night before the Flight Jan 27,1986
- 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
- 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
- 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
- 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
- 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 [email protected] http://kylehailey.com
Editor's Notes
- #2: The bulk of this presentation will be on content from Edward Tufte’s second book were he explores the analysis of the space shuttle disater in 1986 I’ll also bring in industry example (or 2 or 3 if we have time)
- #11: The bulk of the presentaiton is on ideas presented by Edward Tufte in his books But I will also tie in breifly one industry example (or more if I go too fast)
- #12: This is the standard performance report ofr an Oralce database Oracle is by far the best instrumented database in the industry for performance data Other databases offer less Not to mention O/S which typically Presenting such data in meetings can be frustrating I’ve brought these reports ot meetings Pinted to the specific data of interested And explained the solution Only to have eyes glaze over And the meeting continue in arguments for the rest of the meeting
- #13: The geek in me loves this The evangelist and/or educatorß in me , this strikes fear in my heart
- #19: The O-rings of the solid rocket boosers were not designed to erode. Erosion was a clue that something was wrong. Erosion was not something from which safety could be inferred - Richard Feynman
- #20: The O-rings of the solid rocket boosers were not designed to erode. Erosion was a clue that something was wrong. Erosion was not something from which safety could be inferred - Richard Feynman