Real-time marketing analytics with stream processing
Lessons learned from Jewelry TV's application of Hadoop and Spark Streaming
Tuesday, September 19, 2017
Duration: Approximately 60 minutes.
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Using Hadoop and Spark Streaming for data management, Jewelry TV collects and aggregates online customer interactions into a live view. The business is able to utilize streaming data to run real-time analytics that are resulting in increased sales and new marketing insights. The television production staff has been able to upsell and cross-sell related items in real-time.
Join this O'Reilly webcast for a discussion of the lessons learned in applying streaming analytics to online customer interactions. Learn how one organization ingests and processes data in real-time, to deliver marketing analytics that can be acted upon immediately.
You will learn:
About Murthy Mathiprakasam, Director of Product Marketing at Informatica
Murthy Mathiprakasam is a director of product marketing at Informatica and responsible for outbound marketing activities with Informatica's big data products. Murthy has a decade and a half of experience working with emerging high-growth software technologies including roles at Mercury Interactive/HP, Google, eBay, VMware, and Oracle. Murthy holds a master of science in management science from Stanford University, and two bachelor of science degrees in management science and computer science from the Massachusetts Institute of Technology.
About George F. Willard III, Chief Technology Architect at Jewelry Television
As Chief Technology Architect at Jewelry Television, George Willard is a technical leader within Software Engineering, IT Infrastructure, IT Operations, and Data Infrastructure. George works closely with Jewelry Television's executives, product owners, and project management to ensure that 3rd party and in-house developed application and technical architecture meet the project objectives, roadmaps, and long term strategies of Jewelry Television. George is experienced in architecting distributed systems for scalability and performance, with a track record of highly transactional, high-traffic, and high-availability projects in a 24/7 television broadcasting environment.