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

Accelerating analytics and AI from the edge to the cloud (sponsored by Intel)

1:50pm2:30pm Wednesday, March 7, 2018
Location: 230 B

What you'll learn

  • Learn best practices for accelerating analytics and AI
  • Understand how to leverage Intel's technology for AI workloads


Advanced analytics and AI workloads require a scalable and optimized architecture, from hardware and storage to software and applications. Kevin Huiskes and Radhika Rangarajan share best practices for accelerating analytics and AI and explain how businesses globally are leveraging Intel’s technology portfolio, along with optimized frameworks and libraries, to build AI workloads at scale.

This session is sponsored by Intel.

Photo of Kevin  Huiskes

Kevin Huiskes


Kevin Huiskes is the director of marketing in Intel’s Data Center Group. In his 16 years at Intel, Kevin has held a variety of senior business and marketing positions throughout the company, including two years as chief of staff to the executive vice president of Intel’s Data Center Group. His experience includes managing the Intel Data Center Group central marketing organization, managing the Intel Xeon Scalable Processors product line, business development, and a variety of other product management roles. Prior to Intel, Kevin served as a legislative assistant and committee aide to a member of congress in the US House of Representatives. He holds an MBA from Georgetown University and a BA in political science from Wheaton College.

Photo of Radhika Rangarajan

Radhika Rangarajan


Radhika Rangarajan is an engineering director for big data technologies within Intel’s Software and Services Group, where she manages several open source projects and partner engagements, specifically on Apache Spark and machine learning. Radhika is one of the cofounders and the director of the West Coast chapter of Women in Big Data, a grassroots community focused on strengthening the diversity in big data and analytics. Radhika holds both a bachelor’s and a master’s degree in computer science and engineering.