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Sciencing Data

Sciencing Data

A short overview of what Data Science is and some of the kinds of insights we look for at Akamai.

visual data
like spice on a hot griddle
patterns emerge

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Philip Tellis

August 07, 2017
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Transcript

  1. Sciencing Data Acquisition, Distillation & Consumption

  2. Philip Tellis Principal RUM Distiller @ Akamai Author of the

    OpenSource boomerang RUM library twitter:@bluesmoon * github:@bluesmoon
  3. What is Data Science?

  4. A fancy term for Statistics?

  5. A synonym for Computer Science?

  6. A multi-disciplinary Art-Form... combining aspects of Statistics, Computing, Visual Storytelling,

    Domain Expertise, Typography, ,
  7. At Akamai we primarily care about Internet Performance and Security

  8. My team’s speciality is RUM

  9. Search for patterns in data

  10. Find abnormalities by determining what’s normal

  11. Identify the parts of your site most important to your

    users
  12. How does the performance of a website affect user behaviour?

  13. OR ?

  14. None
  15. None
  16. Does emotional state affect our perception of latency?

  17. Real Data • • • • Sports fans can get

    quite emotional!
  18. The US was close to a win but Canada got

    a last minute leg in
  19. But the web audience appeared to be prescient

  20. • • • •

  21. • • •

  22. • • →

  23. But what about Patience?

  24. Definitions Load Time Error Tolerance LD 50 LD 25

  25. Bounce Rate v/s Page Load Time for the entire game

  26. 1st & 2nd Period, Score: 0 - 0

  27. 3rd Period, US Leads 2 - 0

  28. End of 3rd, Canada comes back 2 - 2

  29. Canada wins 3 - 2

  30. patience cultural significance Correlation?

  31. LD 50 values for different countries DE ?? US 5.5s

    UK 11.5s AU ?? CA 13.5s 2.5
  32. The importance of Domain Expertise • structure of a hockey

    game • understanding web performance • biological sciences
  33. Across domains, the Statistics used are often the same

  34. We borrow from Economics The Product Space

  35. ...and Linguistic Anthropology

  36. Navigating the Pacific ocean wind birds cloud star songs stories

    visualizations
  37. Now to the boring stuff...

  38. cleaned • • malicious • anomalous Before we can analyze...

    normalized • population • time-zone • currency
  39. None
  40. Interesting People Data

  41. ★ Understand ★ Borrow ★ ★ ★ story In Conclusion

  42. Philip Tellis Principal RUM Distiller @ Akamai Author of the

    OpenSource boomerang RUM library twitter:@bluesmoon * github:@bluesmoon