DATAx San Francisco 2020
DATAx San Francisco is a cross-industry event for business leaders, strategists, and practitioners looking for best practices and strategic insights to help increase business growth and gain marketplace advantage.
DATAx provides a unique blend of data-focused content tailored to help you find real-world solutions to common challenges.
Our program is specifically curated to examine the most relevant topics on the minds of data scientists and business decision-makers. With an emphasis on collaboration, DATAx is the event where the technical and strategic conversations that change business models are started.
Conference Topics
Strategy and Leadership, Artificial Intelligence, Machine Learning, Deep Learning, Structured and Unstructured Data, Data Driven Culture, Data Governance, Computer Vision, Data Visualization, Natural Language Processing, Data Personalization, Neural Networks, Cryptographic Algorithms, Blockchain, IoT, Customer and Marketing Analytics, Robotics.
DATAx Tracks
TRACK 1: Strategy & Leadership in the Age of Data Dominance
The use of data is reshaping the way companies are doing business. In the age of data dominance business leaders must ensure that data is at the forefront of any business decision. Is your company’s leadership equipped with a data focused strategy plan? Discover how data leaders are defining data governance, establishing data fluency and best practices across their organization.
TRACK 2: Data Science & Artificial Intelligence Working Together
Artificial Intelligence and data are like PB&J perfect together. When AI & data combine amazing insights are discovered. In this track you’ll hear how leading-edge companies are using AI powered data to solve business challenges and make better data informed business decisions.
TRACK 3: Data Utilization: The Art of Extracting Valuable Insights
Data collection is only the beginning of the data journey. Extracting insights is where the real value exists. Join us to learn the methods companies are using to uncover valuable information within their data.
TRACK 4 – Workshops
Upcoming AI & ML Events Newsletter
Monthly to your email. No spam. Trusted by AI & ML experts.
Speakers

Ankit Mangal
Associate Director, Web Analytics, Wayfair

Asma Farooq
Product Lead, Advertising, eBay

Austin Sun
Senior Data Architect & Director of Data Engineering in Advanced Analytics, American Tire Distributors
Bhargav Raman
CEO, Medpixels

Binwei Yang
Distinguished Engineer, Merchant Technology Data Science, Walmart

Carlo Lipizzi, Ph.D
Graduate Engineering Management & Systems Analytics Program Director School of Systems and Enterprises, Stevens Institute of Technology

Carlos Jose Fonseca
SVP Data & Services. Sales Strategy and Solutions Financial, Mastercard

Cathy Tanimura
Sr. Director, Analytics & Data Science, Strava
Chase Kusterer
Professor, Advanced Analytics & Research, Hult International School

Chintan Shah
Vice President of Data Science and Analytics, HYLA, Inc. (“HYLA Mobile”)

Daniel Gremmell
Vice President, Data Science, Plated

DJ Patil
Head of Technology, Devoted Health

Haftan Eckholdt
Chief Data Officer & Chief Science Officer, Understood.org

Jessica B. Lee, Partner
Co-Chair, Privacy, Security & Data Innovations, Loeb & Loeb

Mario Vinasco
Director BI and Analytics, Credit Sesame

Meghan Anzelc
Head of Data and Analytics, Spencer Stuart

Michele Ceru
Data Architect, American Tire Distributors

Michelle Finneran Dennedy
Chief Executive Officer, DrumWave

Morgan Cundiff
Data Scientist, ShopRunner

Dr. Nels Lindahl
Director, Clinical Decision Systems, CVS Health

Sherin Mathews
Senior Data Scientist, Mcafee

Qiaolin Chen
Director of Data Science, Tencent Games

Romy Hussain
Director of Healthcare Economics and Data Science, Johns Hopkins Healthcare

Ronak Shah
Head of Data Engineering, Coursera

Theresa Melvin
Chief Architect, AI-Driven Big Data Solutions, Hewlett Packard Enterprise

Thomas Vincent
Head of Data Science, Getty Images

Vanitha Lucas
Board Member, Viz for Social Good

Vin Vashishta
Data Scientist, Strategist, Author, V2 Machine Learning Consulting

Wade Schulz, MD, PhD
Assistant Professor of Laboratory Medicine & Computational Healthcare Researcher, Yale University School of Medicine
Organizer

Partners




Sponsors



