Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Yael Garten

Yael Garten
Director, Data Science, LinkedIn


Yael Garten leads a team of data scientists at LinkedIn that focuses on understanding and increasing growth and engagement of LinkedIn’s 400 million members across mobile and desktop consumer products. Yael is an expert at converting data into actionable product and business insights that impact strategy. Her team partners with product, engineering, design, and marketing to optimize the LinkedIn user experience, creating powerful data-driven products to help LinkedIn’s members be productive and successful. Yael champions data quality at LinkedIn; she has devised organizational best practices for data quality and developed internal data tools to democratize data within the company. Yael also advises companies on informatics methodologies to transform high throughput data into insights and is a frequent conference speaker. She has a PhD in biomedical informatics from the Stanford University School of Medicine, where her research focused on information extraction via natural language processing to understand how human genetic variations impact drug response. She holds an MSc from the Weizmann Institute of Science in Israel.


11:50am12:30pm Wednesday, March 15, 2017
Data-driven business management, Strata Business Summit
Location: 210 D/H Audience level: Non-technical
Yael Garten (LinkedIn)
Data science is a rewarding career. It's also really hard—not just the technical work itself but also "how to do the work well" in an organization. Yael Garten explores what data scientists do, how they fit into the broader company organization, and how they can excel at their trade and shares the hard and soft skills required, tips and tricks for success, and challenges to watch out for. Read more.
Shirshanka Das (LinkedIn), Yael Garten (LinkedIn)
Garten & Das describe LinkedIn’s learnings on best practices for using Kafka & Hadoop as the foundation of a petabyte-scale data warehouse. Without a principled approach organizations find themselves struggling to deal with evolution of the business. Concrete suggestions will help you process data seamlessly. Beyond technology we discuss experiences running governance to empower data teams.