How The Weather Company leverages billions of data points & predictive analytics

We hear a lot about lambda architectures and how Spark can help us crunch our data both in batch and real-time. After two years in the trenches, Robbie will share how The Weather Company built a general purpose, weather-scale event processing pipeline to make sense of billions of events each day. Inna will follow with a detailed look at how we use that platform to turn raw mobile location data into predictive weather alerts.

Bios:

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Inna Rytsareva is a Data Scientist on the Analytics team at Weather. She has earned a PhD in computer science with expertise in high performance computing and machine learning, making her a true unicorn. Before joining Weather she was a research scientist at the CDC, where she worked on tracking global Hepatitis C outbreaks. She is soon to be a new mom and is looking forward to temporarily trading scatter plots for growth charts.

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Robbie Strickland is VP of Software Engineering at Weather. He has a background in distributed computing, with heavy emphasis on data storage and processing. He has been very involved in the Apache Cassandra project since 2010, and he worked on the original Hadoop-Cassandra integration. He has spoken at numerous conferences and meetups and is the author of Cassandra High Availability. If you want to know how to break your distributed database, he's the guy to talk to.

A link to Robbie's book is below:

http://www.amazon.com/Cassandra-High-Availability-Robbie-Strickland/dp/1783989122