Why Data Science?

79da018530041d04fd59eb3dfee659e3?s=47 Ryan Swanstrom
September 25, 2015

Why Data Science?

A data science presentation given to a local hospital's research department.

79da018530041d04fd59eb3dfee659e3?s=128

Ryan Swanstrom

September 25, 2015
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Transcript

  1. Why Data Science? September 22, 2015

  2. Hello! I am Ryan Swanstrom Data Scientist and Blogger You

    can find me (just about everywhere) at: @ryanswanstrom
  3. More About Ryan ◎ Blogger at Data Science 101 ◎

    Employed by large bank ◎ PhD from SDSU ◎ Guest Blogger ◎ Influential On Twitter (for data science) ◎ Thought Leader by UC Berkeley
  4. None
  5. None
  6. 1. Data Products End Goal of Data Science

  7. Data Product Any tool created with the help of data

    to make a more informed decision
  8. Examples ◎ Dashboards ◎ Spreadsheets (sometimes) ◎ Emails (sometimes) ◎

    People You May Know ◎ Movies to Watch ◎ Many Others
  9. 2. Data Science What is it?

  10. “ Data Science is statistics on a Mac @BigDataBorat 2013

  11. “ Data Scientist (n.) - Person who is better at

    statistics than any software engineer and better at software engineering than any statistician. @josh_wills 2012
  12. “ A Data Scientist is a statistician who lives in

    San Francisco Unknown
  13. Drew Conway’s Venn Diagram http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

  14. Yanir Seroussi http://yanirseroussi.com/2014/10/23/what-is-data-science/

  15. Really, what is data science? According to NIST Data science

    is the empirical synthesis of actionable knowledge from raw data through the complete data lifecycle process. According to NIST Big Data Framework
  16. Simpler Definition of Data Science The creation of data products

  17. Data Science Takes a Team Similar to Sports Specialization is

    important One person cannot do it all
  18. 3. BIG DATA Big Data ≠ Data Science

  19. Three V’s of Big Data ◎ Volume ◎ Velocity ◎

    Variety
  20. “ Data Science doesn’t need big data Ryan Swanstrom Sept.

    22, 2015
  21. 4. Data Science Workflow How to get there?

  22. No Perfect Workflow Question Data Preparation & Cleaning Data Product

    Analysis & Modeling
  23. 5. Data Science Goals Why do data science?

  24. Get All Three ◎ Descriptive ◎ Predictive ◎ Prescriptive

  25. Thanks! I am hoping for questions? You can find me

    everywhere at: @ryanswanstrom
  26. Credits Special thanks to all the people who made and

    released these awesome resources for free: ◎ Presentation template by SlidesCarnival ◎ Photographs by Unsplash & Death to the Stock Photo (license)