Jay Kreps is a Principal Engineer at Linkedin. He was the original author of Voldemort, a distributed key-value storage system recently recognized by the OSCON Data Innovation Award as one of LinkedIn’s major contribution to the open source community to support data analytics.

Jay has also made key contributions to Kafka, a persistent distributed message queue, and Azkaban, a simple batch scheduler for constructing and running Hadoop jobs or other offline processes.

His team builds the core, data-driven features that delight LinkedIn’s users, including People You May Know, Who’s Viewed My Profile, Skill Pages, and the collaborative filtering applications for LinkedIn’s various recommendations.

Gartner predicts that data will grow by 800% in five years, with 80% of it unstructured. The World Economic Forum recently declared big data as an asset class. We’re only getting started to discover the implications of making better sense of large amounts of unstructured data to uncover business opportunities, strategies, and more.

Is big data really an emerging market with lots of innovation, startups, job creation on the horizon? Why did it suddenly become possible? What are the obstacles, and the most promising areas of opportunity? How do you make it real in your organization?

Join this group of thought leaders from Accel Partners, Factual, Greenplum, SAS, @Walmartlabs, and McKinsey Global Institute for a conversation that gets beyond the hype about big data.