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The Next Generation of Data Products | AnacondaCON 2017

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Presented at AnacondaCON 2017 by Hilary Mason, Fast Forward Labs.

Publicado en: Datos y análisis
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The Next Generation of Data Products | AnacondaCON 2017

  1. 1. #OpenDataScienceMeans #AnacondaCON
  2. 2. The Next Generation of Data Products Hilary Mason Fast Forward Labs @hmason hilary@fastforwardlabs.com
  3. 3. What is a data product?
  4. 4. Goodbye, big data!
  5. 5. Hello, AI!
  6. 6. Data products are products that would not be possible without the use of data.
  7. 7. (it’s all the same.)
  8. 8. What makes a great data product?
  9. 9. (it’s boring)
  10. 10. (this is not a solved problem)
  11. 11. What’s different in 2017?
  12. 12. 0 to 1 matters 0 to 1000000 matters
  13. 13. 1) layers of abstraction
  14. 14. [anaconda]
  15. 15. 2) natural language interfaces
  16. 16. 3) data!
  17. 17. + high value problems (don’t forget!)
  18. 18. First, automate things we pay people to do today.
  19. 19. Then, build new products that were simply never viable before.
  20. 20. [caution]
  21. 21. Unfortunately, you can’t just buy good data products.
  22. 22. There is a generic formulation of your problem. Then there’s your problem. This is the data product gap.
  23. 23. It’s hard, and sometimes it doesn’t work.
  24. 24. There are unpredictable edge cases.
  25. 25. Organizations are not designed for data science or for developing data products.
  26. 26. Use an Experimental Development Process.
  27. 27. Find the simplest possible algorithm that will work at scale.
  28. 28. Have a plan for operationalization and maintenance.
  29. 29. There’s a new practice for the UX of ML.
  30. 30. Academic Research Startups Enterprise
  31. 31. Here’s where we look…
  32. 32. 1) a research breakthrough
  33. 33. 2) a change in economics http://www.mkomo.com/cost-per-gigabyte
  34. 34. 3) a capability becomes a commodity
  35. 35. 4) new data is available
  36. 36. Examples
  37. 37. The real impact will be in making complex data simple. There’s been an increase in sales!
  38. 38. Moving beyond counting words to computable representations of concepts.
  39. 39. Tools for combining domain knowledge with small data to make risky decisions.
  40. 40. Hilary Mason @hmason hilary@fastforwardlabs.com
  41. 41. #OpenDataScienceMeans #AnacondaCON

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