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Spark Jeopardy at Zoomdata!

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Donna F.
Spark Jeopardy at Zoomdata!

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Come out and join us for a fun filled evening of Spark Jeopardy at Zoomdata! We’ll divide up in groups to support and back Spark experts / Jeopardy contestants for a fun way to learn Spark. Databricks has kindly helped craft questions and videos to make it interesting (thanks Denny!). Join a team and get to meet some of the most progressive individuals working on Spark solutions today.

Winning team gets cool prizes! We’ll also do a raffle for a free ticket to Strata Hadoop NYC Sep 29-Oct 1.

Pat from Databricks will also be there in person to share a roadmap update:

Pat McDonough is one of Databricks' first employees and focused on helping people build their Spark-based applications and data pipelines. As a member of Databricks for the past two years, he's been lucky enough to see the Spark project grow from a promising incubator to the most active project in Big Data, and to work hand-in-hand with the impressive engineering team that continues to push exciting new technology in to the project, all while learning a few things along the way. Pat previously held positions at Cloudera and Red Hat.

As you come in, you’ll be assigned to one of the below teams led by a Spark expert:

TEAM BAUD - Justin Langseth is CEO of Zoomdata, developers of the fastest visual analytics for Big Data. Zoomdata is Justin's 5th startup--he previously founded Strategy.com, Claraview, Clarabridge, and Augaroo. Justin is an expert in big data, business intelligence, text analytics, sentiment analytics, and real-time data processing. He graduated from MIT with a degree in Management of Information Technology, and holds 14 patents. He is eagerly awaiting the singularity to increase his personal I/O rate which is currently frustratingly pegged at about 300 baud.

TEAM MARVEL - Ted Malaska is a Principal Solutions Architect with Cloudera. He has spent the last four years working with Hadoop and supporting over 40 clients with their Big Data implementations, some with over 200 clusters. He is the co-author of the O’Reilly book "Hadoop Application Architecture" which features Apache Spark in three of the nine chapters. He is also an active contributor to over nine Hadoop Ecosystem projects including two minor contributions to Spark. At Cloudera, he has been very involved with multiple Spark applications for customers and he has gained experience with Spark, Spark-GraphX, and Spark Streaming. Ted is also a Marvel Fan Boy and runner.

TEAM NEURO - Jeremy Freeman is a neuroscientist at the intersection of biology, computation, data science, and visualization. He wants to understand how the brain supports complex behavior, and how it might inform the design of intelligent systems. He’s also passionate about open source and open science, contributing to major open source big data technologies, building platforms for collaborative data sharing and analysis, and advising scientists and developers across a range of fields. Jeremy is an avid supporter of Spark and has presented in many Spark events.

And serving as Alex Trebek:

Andrew Psaltis has a wealth of experience in software design, and in the construction of large-scale data-intensive systems. He is deeply entrenched in streaming systems and obsessed with delivering insight at the speed of thought. As the author of Streaming Data (http://manning.com/psaltis/) by Manning and an international speaker he spends most of his waking hours thinking about, writing about, and building streaming systems. He was the primary architect of Webtrends Streams -- the first scalable streaming architecture pushing real-time visitor and event-level digital intelligence into the marketing ecosystem. Andrew currently supports MetiStream as a Sr. Architect and Spark Trainer. When he's not busy being busy, he's spending time with his lovely wife, two kids, coaching and watching as much Lacrosse as possible.

This is going to be a fun night and I can't wait to see you!

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We're proud to partner w/ #StrataHadoop NYC Sep 29-Oct 1. Save 20% w/code UGDCSPARK http://oreil.ly/1KC2sCB

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