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Agenda

Sessions

Day 1

September 21st

9:00 am
UTC-5
Welcome / State of Business Intelligence
Speakers: Chris von Simson, Howard Dresner
Session info
9:45 am
UTC-5
Break / Expo
10:15 am
UTC-5
Data Action: Using Data for a Public Good
Speaker: Professor Sarah Williams
Session info
11:30 am
UTC-5
Lunch Break/Expo
12:30 pm
UTC-5
Winning at Data with a Modern Strategy
Speaker: David Dadoun
Session info
1:30 pm
UTC-5
Break/Expo
2:00 pm
UTC-5
Round Table Discussions
Session info
3:00 pm
UTC-5
Break/Expo
3:30 pm
UTC-5
See the World, Change the World: Data at a Planetary Scale
Speaker: Dr. Tanya Harrison
Session info
6:00 pm
UTC-5
Reception - Hosted by Alation

Day 2

September 22nd

9:00 am
UTC-5
Welcome Back / Data Leadership
Speakers: Chris von Simson, Howard Dresner
Session info
9:30 am
UTC-5
Workshop: Connect Data, Actions, and Outcomes for a Better World
Speaker: Dr. Lorien Pratt
Session info
11:00 am
UTC-5
Break/Expo
11:30 am
UTC-5
Your Data Should Show up for Work More Often
Speaker: Dr. Laura Downey
Session info
12:30 pm
UTC-5
Lunch
1:30 pm
UTC-5
Workshop: Presenting Data Effectively
Speaker: Dr. Stephanie Evergreen
Session info
3:00 pm
UTC-5
Break/Expo
3:30 pm
UTC-5
Round Table Discussions
Session info
4:30 pm
UTC-5
Step Up and Start Your CDO Journey
Speakers: Courtney Moores, Stefanie Costa Leabo
Session info
5:45 pm
UTC-5
Announcements
6:00 pm
UTC-5
Closing

Data Action: Using Data for a Public Good

Professor Sarah Williams

Big data can be used for good–from tracking disease to exposing human rights violations–and for bad–implementing surveillance and control. Data inevitably represents the ideologies of those who control its use; data analytics and algorithms too often exclude women, the poor, and ethnic groups.

In Data Action, Sarah Williams provides a guide for working with data in more ethical and responsible ways. Too often data has been used–and manipulated–to make policy decisions without much stakeholder input.

Williams outlines a method that emphasizes collaboration among data scientists, policy experts, data designers, and the public. This approach creates trust and co-ownership in the data by opening the process to those who know the issues best.