This is a proposed workflow for data science projects and a specific use case where that framework helped a nonprofit and DataKind complete a successful data science project. Data Science Workflow: 1. Ask 2. Acquire 3. Process 4. Model 5. Deliver Dr. Brian Spiering is a Data Science Faculty member at GalvanizeU which, in cooperation with the University of New Haven, offers an accredited Master’s degree program in Data Science.

1. Dr. Brian Spiering
Nonprofit Edition
A DATASCIENCE WORKFLOW:

2. Hi, I’m Brian.
Faculty @GalvanizeU
brian.spiering@galvanize.com
@BrianSpiering

3. A Data Science Workflow
Ask1
Acquire2
Process3
Model4
Deliver5

4. Ask
1
Start by asking the right questions

5. How can Data Science be a
force multiplier for good?

6. Acquire
2
Find the right team & obtain the proper data

7. Adam Crawley Eric Williams

8. Citizen Science for Tracking Flu

9. Process
3
Create a structure to empower the team
(and clean the data)

11. Model
4
Leverage your team to find meaning in the data

15. Deliver
5
Make sure what you make has value

16. “Flusion” Report for Health Authorities

17. “Flusion” Report for Health Authorities

18. “Flusion” Report for Health Authorities

19. A Data Science Workflow
Ask1
Acquire2
Process3
Model4
Deliver5

20. Life is nonlinear
(your process should be, too)

21. Thank You!