Practical problem solving with data involves more than just visualization or applying the latest machine learning techniques. Intuition, domain knowledge, and reasonable approximations can mean the difference between a successful model and a catastrophic failure. Good problem solvers deeply analyze available data, improvise solutions using their unique assets, anticipate outcomes and issues, and adapt their techniques over time.

1. Practical Problem
Solving With Data
Pete Skomoroch
@peteskomoroch
Onlab Data Conference
June 22, 2012

4. To solve hard problems:

5. Think like a street
fighter

6. Analyze
Improvise
Anticipate
Adapt

7. How does this apply to
startups?

8. Analyze

9. The Men Who Stare at Charts

10. Look at your data

12. Averages Suck
12"
10"
8"
6"
4"
2"
0"
1" 2" 3" 4" 5" 6" 7" 8" 9" 10"

13. Build a Viewer App

15. Algorithmic Intuition

16. Improvise

21. Extract

23. Anticipate

26. Use Your Viewer App

27. Adapt

28. Look at your errors

29. • Sanity check row counts
• Track errors over time
• Find patterns in the error data
• Add missing features to models
• Replace models entirely

31. Analyze
Improvise
Anticipate
Adapt

32. Think like a
street fighter
Pete Skomoroch
@peteskomoroch
Onlab Data Conference
June 22, 2012