Session 1 of the Applied Data Science Invited Talks Track
Monday 10AM – August 15, 2016 – Yosemite Room – Hilton San Francisco
The introductory article in this blog series can be found here.
Did you ever wonder: What does it take to make Data Science work in a large enterprise? What are the big guys doing at big scale? How about the promise of Social Sciences and their applications to understanding the social networks and human behavioral phenomena on the web? Then this session is for you!
We launch the Applied Data Science Invited Talks Track Talks with our first session this morning. Come to Yosemite Room at the Hilton at 10AM and learn all about some of the exciting topics in Data Science and what it takes to get real deployments in place and successfully.
Our first speaker is Jonathan Becher (@jbecher), Chief Digital Officer, SAP. Jon’s talk is titled: “Can You Teach The Elephant To Dance? AKA: Culture Eats Data Science For Breakfast”. Jon is a long-time analytics veteran having run also run his own analytics companies as CEO prior to joining SAP (see his bio here). He and will talk to us about what it takes to truly institutionalize a data-driven culture at a large organization. He argues that changing the heart of how a company operates requires more than just process or technology changes: It requires cultural changes. And these cultural changes usually trigger corporate antibodies adverse to anything new. Jon will share some lessons learned over his career and will review key practical realities of instituting data-driven decisions in a very large multi-national company.
Our second speaker is Jeff Striblingof Verizon who is substitution for Ashok Srivastava, Chief Data Scientist at Verizon who could not make it in person due to a family emergency. Jeff is Associate Director of Product Management and leads Verizon’s Product for the Big Data and Analytics group. He and his team are developing big data products in the areas of advertising, IoT, cybersecurity and network health management, based on scalable machine learning algorithms. Jeff will talk to us about recent innovations in large-scale machine learning and their applications on massive, real-world data sets at Verizon. These applications power new revenue generating products and services for the company and are hosted on a massive computing and storage platform known as Orion. He will discuss the architecture of Orion and the underlying algorithmic framework. We will also cover some of the real-world aspects of building a new organization dedicated to creating new product lines based on data science.
Our last speaker in this session is Duncan Watts, Principal Researcher at Microsoft. Duncan has been a major figure in the world that is at the intersection of Sociology and Computation. I first got to know Duncan and his great work at Yahoo! Research and you can see his bio here. Duncan will talk to us about the new emerging field of “Computational Social Science (CSS).” He addresses his thoughts towards the “big” questions that motivated the field in the first place—questions concerning systemic risk in financial systems, problem solving in complex organizations, and the dynamics of epidemics or social movements, among others. He argues that in spite of many thousands of published papers, there has been progress here. He highlights some examples of research that would not have been possible just a handful of years ago and that illustrate the promise of CSS. He concludes with some thoughts on how CSS can bridge the gap between its current state and its potential.
We hope to see you at the Applied Data Science Invited Talks track in the Yosemite conference room of the Hilton, Union Square, San Francisco and we invite you to come and ask the tough questions of our speakers.
See you at 10AM!
Usama, Rajesh and Evangelos – co–chairs of Invited Talks Track
Read the next Blog in the series by clicking HERE
Come to our Interactive Panels Program as part of the Applied Data Science Track on Tuesday Afternoon, August 16, 2016:
Read about the Invited Panel: The Myths & Reality of BigData Tools
Read about the Invited Panel: BigData Needs Big Dreamers: Lessons from BigData Investors