1. Democratizing Data: Expanding Opportunities for Students in Data Science
Robin Angotti, Johnny Arenas, Dion Thompson

2. Setting the Stage

3. Location, Location, Location

4. UWB 5995 students, 55 undergraduate and graduate degree programs
48% underrepresented minorities, 10 % international students, 40% white, and 2% are not identified
45% of Freshmen and 41% of transfer students are 1st generation college students
35% of Freshman and 32% of transfer students are pell eligible

5. Data Science: Hottest Job, Scarcest Talent

6. What is Democratization of Data Science?
“‘Democratizing data science’, in our view, means ensuring that our discipline promotes the common good, which is often beyond the narrow commercial and demographic interests of the groups that most frequently use data science today. ” (Chou, Li, & Sridharan, 2014)
“People who know the data should be the ones to ask the questions of the data.” - Tableau

7. The Disconnect…
Lots of people have questions of data but lack the quantitative knowledge and analytical skills to be able to answer their questions
UWB students have the quantitative knowledge and analytical skills but don’t have access to real data or understand the situation or question that is being asked of the data

8. The Question…
Is it possible to teach students data science skills when they have a background that includes a single statistics course simultaneously while they are working as data scientists?
Real Clients
Ongoing, Iterative Communication
Cleaning
Privacy
Visualization Techniques
Analysis Techniques

9. Hi, I’m Johnny… Business major (Marketing and Finance)
Little to no previous background in data analytics
No previous research experience
Real Change (Seattle Newspaper)
I <3 Tableau

10. What have I learned? >Survey questions
>Strong communication required
>Ask questions
>Interactivity is nice
>No pi charts, please, seriously
>If your grandma can understand it, you did great ☺
>Privacy is important

11. Hi I’m Dion... 3x small business owner
Former student government representative
Applied computing (computer science) major
No previous data science/analytics experience
Placement test data

14. Overall take away of the process
Ask good questions your client
Create a realistic timeline
Clean data sooner rather than later
Stick to the original question
“Less is more” especially when it comes to visualization

15. Data Science Skills What experience are they gaining?
Communication with real clients
Teamwork
Curiosity
Working with Unstructured Data
Data Visualization
What are they NOT gaining?
Machine Learning/AI
SQL
Hadoop
Python

16. QUESTIONS?
References
Chou, S., Li, W., Sridharan, R.: Democratizing data science. In: Proceedings of the KDD th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA. pp. 24–27.