This document discusses challenges with a data science project including the experimental and unpredictable nature, difficulties with scheduling due to unknown completion times, proposing new products with data and technology limitations, and addressing failures by breaking the work into smaller pieces with increased visibility and producing functional interim results to stay on track.

1. Data Science Project

2. Data Science is experimental

3. Ambiguous and unpredictable!
What to do?
Do you find the best idea?
Do you have good results?

4. Scheduling almost impossible !
When you’ll be done?

5. +

7. Propose a new product?
Limitation of data and technology?

8. Break down into smallpieces
Increase visibility!

9. Makeit work!
Produceasomething thatfunctionsenough tokeep youontrack

10. Acknowledgefailure
Figure out what to do next!