Big data big_skills_data_visualization

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  • 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
  • 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
  • Big data big_skills_data_visualization

    1. 1. Midnight January 28, 1986 Lives are on the line Thanks to Edward Tufte Night before the Flight Jan 27,1986 Importance of Data Visualization
    2. 2. Estimated launch temperature 29º
    3. 3. 13 Pages Faxed
    4. 4. 13 Pages Faxed 3 different types of names
    5. 5. Damage (in overwhelming detail) but No Temperatures 13 Pages Faxed
    6. 6. 13 Pages Faxed Test engines, not launches, fired horizontally Missing temperatures for 5 erosion damage flights Temperatures but limited Damage
    7. 7. 13 Pages Faxed “blow by”, not more important “erosion”, (at hottest and coldest launches)
    8. 8. 13 Pages Faxed Predict Temperature Recommendation
    9. 9. 55 65 7560 70 80 1 Original Engineering data 2 3 damages atdamages at the hottestthe hottest and coldestand coldest temperaturetemperature -- managementmanagement Would you launch?
    10. 10. Congressional Hearings Evidence No Damage Legend Damage hard to read
    11. 11. Congressional Hearings Evidence Temperature correlation difficult
    12. 12. 55 65 7560 70 80 1 Original Data 2 3
    13. 13. Clearer 1. Y-Axis amount of damage (not number of damage) 55 65 7560 70 80 4 8 12
    14. 14. 1. Y-Axis amount of damage (not number of damage) 2. Include successes 55 65 7560 70 80 4 8 12 Clearer
    15. 15. 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
    16. 16. 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
    17. 17. 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
    18. 18. 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
    19. 19. 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
    20. 20. Difficult  NASA Engineers Fail  Congressional Investigators Fail  Data Visualization is Difficult But … Lack of Clarity can be devastating
    21. 21. Counties in US  3101 Counties  50 pages “The humans … are exceptionally good at parsing visual information.” Knowledge representation in cognitive science. Westbury, C. & Wilensky, U. (1998)
    22. 22. “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
    23. 23. Graphics for Anscombe’s Quartet
    24. 24. Do You Want? Engineering Data?Engineering Data?
    25. 25. Pretty PicturesPretty Pictures Do You Want?
    26. 26. Clean and ClearClean and Clear ? ? ? ?? ? ? ? ? ?? ? Do You Want?
    27. 27. 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? Tuning the Database Anscombe's Quartet I II III IV x y x y x y x y 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 ComplexComplex AveragesAverages
    28. 28. 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 :
    29. 29. How Can We Open the Black Box? Max CPU (yard stick) Top ActivityTop Activity SQLSQL SessionsSessions LOADLOAD

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