Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Schedule: Case studies sessions

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9:00am–5:00pm Tuesday, March 26, 2019
Data Case Studies
Location: 2022
Alex Kudriashova (Astro Digital), Jonathan Francis (Starbucks), JoLynn Lavin (General Mills), Robin Way (Corios), June Andrews (GE), Kyungtaak Noh (SK Telecom), Taposh DuttaRoy (Kaiser Permanente), Sabrina Dahlgren (Kaiser Permanente), Craig Rowley (Columbia Sportswear), Ambal Balakrishnan (IBM), Benjamin Glicksberg (UCSF), Patrick Lucey (Stats Perform), Rhonda Textor (True Fit)
Hear practical insights from household brands and global companies: the challenges they tackled, approaches they took, and the benefits—and drawbacks—of their solutions. Read more.
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9:00am–5:00pm Tuesday, March 26, 2019
Strata Data Ethics Summit
Location: 2024
Susan Etlinger (Altimeter Group), Alistair Croll (Solve For Interesting), Susan Etlinger (Altimeter Group), Jake Metcalf (Ethical Resolve), Emanuel Moss (Data & Society), Bradley Voytek (UC San Diego ), Jonathan Foster (Microsoft), Yiannis Kanellopoulos (Code4Thought), Kathy Baxter (Salesforce), Bulbul Gupta (Socos Labs), Brian Rieger (Labelbox), Carole Piovesan (INQ Data Law), Jana Eggers (Nara Logics), Irina Raicu (Santa Clara University), Brian Green (Santa Clara University), Alistair Croll (Solve For Interesting), Susan Etlinger (Altimeter Group), Tim O'Reilly (O'Reilly Media), Bradley Voytek (UC San Diego ), Jana Eggers (Nara Logics), Jonathan Foster (Microsoft), Brian Rieger (Labelbox), Rachel Thomas (fast.ai), Yiannis Kanellopoulos (Code4Thought), Rumman Chowdhury (Accenture), Kathy Baxter (Salesforce), Carole Piovesan (INQ Data Law), Stuart Buck (Arnold Ventures)
In this day-long event, academics, practitioners, and innovators dive deep into the thorny issues of data, privacy, bias, and morality that are at the forefront of today's headlines. Read more.
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11:00am–11:40am Wednesday, March 27, 2019
Recommendation engines and mobile gaming
Location: 2024
Secondary topics:  Media, Marketing, Advertising
Bysshe Easton (KIXEYE), Thomas Dobbs (KIXEYE)
Average rating: ****.
(4.50, 2 ratings)
As a fully closed model economy, games offer a unique opportunity to use analytics to create unique purchase opportunities for customers. Bysshe Easton and Thomas Dobbs explain how KIXEYE uses machine learning to create personalized offer recommendations for its customers, resulting in significantly increased monetization and retention. Read more.
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5:10pm–5:50pm Wednesday, March 27, 2019
Purchase, play, and upgrade data for video game players
Location: 2024
Secondary topics:  Media, Marketing, Advertising
Eric Bradlow (The Wharton School), Zachery Anderson (Electronic Arts)
Average rating: ***..
(3.00, 1 rating)
Eric Bradlow and Zachery Anderson discuss the Wharton Customer Analytics Initiative research opportunity process and explain how some of EA’s solved some of its business problems by sharing its data with 11 teams of researchers from around the world. Read more.
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2:40pm–3:20pm Thursday, March 28, 2019
Community and regional data sharing policy frameworks: Frontier stories
Location: 2018
Secondary topics:  Health and Medicine, Open Data, Data Generation and Data Networks
Mei Fung (People Centered Internet)
Average rating: ****.
(4.67, 3 ratings)
Data sharing necessitates stakeholders and populations of people to come together to learn the benefits, risks, challenges, and known and unknown "unknowns." Data sharing policies and frameworks require increasing levels of trust, which takes time to build. Join Mei Fung for trail-blazing stories from Solano County, California, and ASEAN (SE Asia), which offer important insights Read more.
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4:40pm–5:20pm Thursday, March 28, 2019
Bringing data to life: Combining machine learning and art to tell a data story
Location: 2007
Secondary topics:  Streaming, realtime analytics, and IoT, Text and Language processing and analysis, Visualization, Design, and UX
Nancy Rausch (SAS)
Average rating: ****.
(4.80, 5 ratings)
For data to be meaningful, it needs to be presented in a way that people can relate to. Nancy Rausch explains how she combined streaming data from a solar array and machine learning techniques to create a live-action art piece—an approach that helped bring the data to life in a fun and compelling way. Read more.