Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Big data analytics and machine learning techniques to drive and grow business

Burcu Baran (LinkedIn), Wei Di (LinkedIn), Michael Li (LinkedIn), Chi-Yi Kuan (LinkedIn)
9:00am12:30pm Tuesday, March 6, 2018

Who is this presentation for?

  • Business leaders, researchers, and practitioners

What you'll learn

  • Understand the big data analytics lifecycle
  • Learn how to utilize state-of-the-art techniques to drive and grow business

Description

Analytics is the discovery, interpretation, and communication of actionable insights from big data. LinkedIn’s mission is to drive understanding and impactful decision making through rigorous use of data. Our analytics is deeply tied to core modules of our ecosystem, including product, marketing, and sales.

Burcu Baran, Wei Di, Michael Li, and Chi-Yi Kuan walk you through the big data analytics and data science lifecycle and share their experience and lessons learned leveraging advanced analytics and machine learning techniques such as predictive modeling to drive and grow business at LinkedIn. You’ll learn how to empower business partners to access data and insights whenever needed, how to optimize business performance by leveraging unique data, and how to innovate the way that analytics help grow businesses.

Topics include:

  • An introduction to data analytics and data science
  • Product analytics, both consumer and enterprise
  • Machine learning modeling
Photo of Burcu Baran

Burcu Baran

LinkedIn

Burcu Baran is a senior data scientist on LinkedIn’s analytics data mining team. Burcu is passionate about bringing mathematical solutions to business problems using machine learning techniques. Previously, she worked on predicting modeling at a B2B business intelligence company and was a postdoc in the Mathematics Departments at both Stanford and the University of Michigan. Burcu holds a PhD in number theory.

Photo of Wei Di

Wei Di

LinkedIn

Wei Di is a staff member on LinkedIn’s business analytics data mining team. Wei is passionate about creating smart and scalable solutions that can impact millions of individuals and empower successful business. She has wide interests covering artificial intelligence, machine learning, and computer vision. Previously, Wei worked with eBay Human Language Technology and eBay Research Labs, where she focused on large-scale image understanding and joint learning from visual and text information, and worked at Ancestry.com in the areas of record linkage and search relevance. Wei holds a PhD from Purdue University.

Photo of Michael Li

Michael Li

LinkedIn

Michael Li is head of analytics at LinkedIn, where he helps define what big data means for LinkedIn’s business and how it can drive business value through the EOI analytics framework. Michael is passionate about solving complicated business problems with a combination of superb analytical skills and sharp business instincts. His specialties include building and leading high-performance teams to quickly meet the needs of fast-paced, growing companies. Michael has a number of years’ experience in big data innovation, business analytics, business intelligence, predictive analytics, fraud detection, analytics, operations, and statistical modeling across financial, ecommerce, and social networks.

Photo of Chi-Yi Kuan

Chi-Yi Kuan

LinkedIn

Chi-Yi Kuan is director of business analytics at LinkedIn. He has over 15 years of extensive experience in applying big data analytics, business intelligence, risk and fraud management, data science, and marketing mix modeling across various business domains (social network, ecommerce, SaaS, and consulting) at both Fortune 500 firms and startups. Chi-Yi is dedicated to helping organizations become more data driven and profitable. He combines deep expertise in analytics and data science with business acumen and dynamic technology leadership.

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