Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY

Schedule: Law, ethics, governance sessions

4:35pm5:15pm Wednesday, September 27, 2017
Location: 1A 06/07 Level: Intermediate
Patrick Hall (H2O.ai | George Washington University), SriSatish Ambati (H2O.ai)
Average rating: *****
(5.00, 1 rating)
Interpreting deep learning and machine learning models is not just another regulatory burden to be overcome. People who use these technologies have the right to trust and understand AI. Patrick Hall and Sri Satish share techniques for interpreting deep learning and machine learning models and telling stories from their results. Read more.
11:20am12:00pm Thursday, September 28, 2017
Location: 1E 15/16 Level: Beginner
Secondary topics:  Data for good, Smart cities
Daniel Goddemeyer (OFFC NYC), Dominikus Baur (Freelance)
Increasing access to our personal data raises profound moral and ethical questions. Daniel Goddemeyer and Dominikus Baur share the findings from Data Futures, an MFA class in which students observed each other through their own data, and demonstrate the results with a live experiment with the audience that showcases some of the effects when personal data becomes accessible. Read more.
1:15pm1:55pm Thursday, September 28, 2017
Location: 1E 15/16 Level: Intermediate
Steven Ross (Cloudera), Mark Donsky (Okera)
Average rating: ****.
(4.00, 3 ratings)
In May 2018, the General Data Protection Regulation (GDPR) goes into effect for firms doing business in the EU, but many companies aren't prepared for the strict regulation or fines for noncompliance (up to €20 million or 4% of global annual revenue). Steven Ross and Mark Donsky outline the capabilities your data environment needs to simplify compliance with GDPR and future regulations. Read more.
2:05pm2:45pm Thursday, September 28, 2017
Location: 1A 21/22 Level: Intermediate
Sneha Rao (Spotify), Joel Östlund (Spotify)
Spotify makes data-driven product decisions. As the company grows, the magnitude and complexity of the data it cares for the most is rapid increasing. Sneha Rao and Joel Östlund walk you through how Spotify stores and exposes audience data created from multiple internal producers within Spotify. Read more.
2:05pm2:45pm Thursday, September 28, 2017
Location: 1E 15/16 Level: Intermediate
Majken Sander (Majken Sander)
Average rating: ***..
(3.00, 3 ratings)
Personal data is increasingly spread across various services globally. But what do companies know about us? And how do we collect that knowledge, get ahold of our own data, and maybe even correct faulty perceptions by putting the right answers out there as a service? Majken Sander explains why we desperately need a personal Discovery Hub: a go-to place for knowledge about ourselves. Read more.
2:55pm3:35pm Thursday, September 28, 2017
Location: 1A 01/02 Level: Intermediate
Secondary topics:  Media
Shirshanka Das (LinkedIn), Tushar Shanbhag (LinkedIn)
Shirshanka Das and Tushar Shanbhag explore the big data ecosystem at LinkedIn and share its journey to preserve member privacy while providing data democracy. Shirshanka and Tushar focus on three foundational building blocks for scalable data management that can meet data compliance regulations: a central metadata system, an integrated data movement platform, and a unified data access layer. Read more.