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Push It to the Limit: Operationalizing Your Models in Promote

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Wish you could easily deploy predictive models so people can use them? In this session, get an overview of Promote and see how it can help you take care of business. Ross Kippenbrock walks you through a statistical model, deploying a version of the model from all three of the clients (Designer, Python, R), and then demonstrates how this looks in a real-world setting with a demo of a web application that uses this model.

Ross Kippenbrock - Manager, Software Engineering, Alteryx

Published in: Data & Analytics
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Push It to the Limit: Operationalizing Your Models in Promote

  1. 1. # A L T E R Y X 1 9 PRESENTED BY PUSHING IT TO THE LIMIT: OPERATIONALIZING YOUR MODELS IN PROMOTE Ross Kippenbrock rkippenbrock@alteryx.com
  2. 2. # A L T E R Y X 1 9 FORWARD-LOOKING STATEMENTS This presentation includes “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. These forward-looking statements may be identified by the use of terminology such as “believe,” “may,” “will,” “intend,” “expect,” “plan,” “anticipate,” “estimate,” “potential,” or “continue,” or other comparable terminology. All statements other than statements of historical fact could be deemed forward-looking, including any projections of product availability, growth and financial metrics and any statements regarding product roadmaps, strategies, plans or use cases. Although Alteryx believes that the expectations reflected in any of these forward-looking statements are reasonable, these expectations or any of the forward-looking statements could prove to be incorrect, and actual results or outcomes could differ materially from those projected or assumed in the forward-looking statements. Alteryx’s future financial condition and results of operations, as well as any forward-looking statements, are subject to risks and uncertainties, including but not limited to the factors set forth in Alteryx’s press releases, public statements and/or filings with the Securities and Exchange Commission, especially the “Risk Factors” sections of Alteryx’s Quarterly Report on Form 10-Q. These documents and others containing important disclosures are available at www.sec.gov or in the “Investors” section of Alteryx’s website at www.alteryx.com. All forward-looking statements are made as of the date of this presentation and Alteryx assumes no obligation to update any such forward-looking statements. Any unreleased services or features referenced in this or other presentations, press releases or public statements are only intended to outline Alteryx’s general product direction. They are intended for information purposes only, and may not be incorporated into any contract. This is not a commitment to deliver any material, code, or functionality (which may not be released on time or at all) and customers should not rely upon this presentation or any such statements to make purchasing decisions. The development, release, and timing of any features or functionality described for Alteryx’s products remains at the sole discretion of Alteryx.
  3. 3. # A L T E R Y X 1 9 3 With Alteryx, I can deploy my machine learning models into production apps! ROSS KIPPENBROCK When I use Alteryx, I feel empowered. A L T E R Y X U S E R S I N C E 2 0 1 6
  4. 4. # A L T E R Y X 1 9 4 TODAY’S AGENDA 1. Use Cases 2. Why would I want to deploy models? 3. Problems with model deployment 4. Legacy solutions for model deployment 5. How does Promote fit in? 6. Example application
  5. 5. # A L T E R Y X 1 9 USE CASES 5
  6. 6. # A L T E R Y X 1 9 MORE USE CASES 6
  7. 7. # A L T E R Y X 1 9 DATA SCIENCE LIFECYCLE 7 01 0402 03 OBTAIN DATA MODEL DATA EXPLORE DATA MODEL DEPLOYMENT
  8. 8. # A L T E R Y X 1 9 MODEL DEPLOYMENT 8 REPORTS INT E RACT IVE DASHBOARDS RE AL- T IM E
  9. 9. # A L T E R Y X 1 9 SO MANY LOST MODELS 9
  10. 10. # A L T E R Y X 1 9 SO MANY LOST MODELS 10
  11. 11. # A L T E R Y X 1 9 11 WHY IS MODEL DEPLOYMENT HARD?
  12. 12. # A L T E R Y X 1 9 MEET TREY, THE DATA SCIENTIST 12 Hi, I’m Trey.
  13. 13. # A L T E R Y X 1 9 MEET TREY’S BOSS, STEVE 13 We need to reduce churn. Okay. I'll look into it.
  14. 14. # A L T E R Y X 1 9 THE “A HA” MOMENT ISN’T THE END 14 I figured out that....some complex stuff about vector space that'll improve... ....and that's how we'll reduce churn. Sounds good. Let's do that...
  15. 15. # A L T E R Y X 1 9 TREY TALKS WITH ENGINEERS 15 Anyone know what Gradient Boosting is? So when can we go live with the new model?
  16. 16. # A L T E R Y X 1 9 16
  17. 17. # A L T E R Y X 1 9 17 HOW DO WE DEPLOY THESE MODELS?
  18. 18. # A L T E R Y X 1 9 18 1) TRANSLATE
  19. 19. # A L T E R Y X 1 9 19
  20. 20. # A L T E R Y X 1 9 20 2 REBEL POLICEMEN 2
  21. 21. # A L T E R Y X 1 9 21 DEPLOYMENTS CAN TAKE MONTHS
  22. 22. # A L T E R Y X 1 9 22 2) PMML
  23. 23. # A L T E R Y X 1 9 23 ?
  24. 24. # A L T E R Y X 1 9 24
  25. 25. # A L T E R Y X 1 9 25 3) ROLL YOUR OWN
  26. 26. # A L T E R Y X 1 9 26 BUILDING FOR HIGH AVAILABILITY IS HARD
  27. 27. # A L T E R Y X 1 9 27 THIS IS WHY WE BUILT PROMOTE PROMOTE
  28. 28. # A L T E R Y X 1 9 28 MAKE PREDICTIONS PREDICTIVE MODELS DATA SCIENCE & ANALYTICS TEAMS FRONT-LINE EMPLOYEES MARKETERS CUSTOMERS PROMOTE Code Free & Code Friendly APPLICATIONS
  29. 29. # A L T E R Y X 1 9 29 PROMOTE AT THE CORE DEPLOY PREDICTIVE MODELS DATA SCIENCE & ANALYTICS TEAMS API-invoked function execution PROMOTE
  30. 30. # A L T E R Y X 1 9 30 PROMOTE AT THE CORE SEND REQUEST DATA SCIENCE & ANALYTICS TEAMS API-invoked function execution PROMOTE MODEL RESPONSE
  31. 31. # A L T E R Y X 1 9 31 PREDICTING GOAL PROBABILITY IN NHL GAMES DEMO PROMOTE
  32. 32. # A L T E R Y X 1 9 32
  33. 33. # A L T E R Y X 1 9 PROBABILITY OF SCORING: 3.2% 33
  34. 34. # A L T E R Y X 1 9 34 FEATURES OF A SHOT SHOT DISTANCE SHOT ANGLE
  35. 35. # A L T E R Y X 1 9 SHOT TYPES 35
  36. 36. # A L T E R Y X 1 9 THE DATA & MODEL 36
  37. 37. # A L T E R Y X 1 9 WEB APPLICATION 37 React Frontend App Promote Model Node.js Backend
  38. 38. # A L T E R Y X 1 9 38 ADDITIONAL RESOURCES https://github.com/rkipp1210/alteryx-inspire-2019
  39. 39. # A L T E R Y X 1 9 THANK YOU rkippenbrock@alteryx.com 39 ROSS KIPPENBROCK
  40. 40. # A L T E R Y X 1 9 COMPLETE SESSION SURVEYS ATTENTION 40 You were handed a survey as you entered the room. It should take less than 2 minutes to complete Please return your completed surveys B E F O R E YO U L E AV E the room Surveys are anonymous, and we rely on your opinion for improvement
  41. 41. # A L T E R Y X 1 9 BEFORE YOU LEAVE ATTENTION 41 B E F O R E YO U L E AV E … please take a moment to complete your evaluation survey. Hand it to the room monitors on your way out.

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