This meetup focuses on Scalability and technologies to enable handling large amounts of data: Hadoop, HBase, distributed NoSQL databases, and more!
There's not only a focus on technology, but also everything surrounding it including operations, management, business use cases, and more.
We've had great success in the past, and are growing quickly! Previous guests were from Twitter, LinkedIn, Amazon, Cloudant, Microsoft, 10gen/MongoDB, and more.
This month's guests:
Nick Dimiduk, Hortonworks -- HBase Application Development
Get a sneak peek at what's in store for the developer using HBase as a backing datastore for web apps. We'll review the standard HBase client API before going into a framework architecture that makes HBase development more like other frameworks designed for developer productivity. We'll go over fundamentals like rowkey design and column family considerations but we'll also dig into how we can tap coprocessors to add functionality to our apps that otherwise might normally be overlooked.
Bio: Nick Dimiduk is an engineer and hacker with a respect for customer-driven products. I started using HBase before it was a thing, and co-wrote HBase in Action to share that experience. I studied Computer Science & Engineering at The Ohio State University, specifically programming languages, and artificial intelligence.
Paul Hofmann, Saffron - Sense Making And Prediction Like The Human Brain
Abstract: There is growing interest in automating cognitive thinking, but can machines think like humans? Associative memories learn by example like humans. We present the world's fastest triple store -SaffronMemory Base- for just in time machine learning. Saffron Memory Base uncovers connections, counts and context in the raw data. It builds out of the box a semantic graph from hybrid data sources. Saffronstores the graph and its statistics in matrices that can be queried in real time even for Big Data. Connecting the DotsWe demonstrate the power of entity rank for real time search by the example of the London Bomber and Twitter sentiment analysis. Illuminating the Dots We show the power of Saffron's model free approach for pattern recognition and prediction on a couple of real world examples like Boeing's use case of predictive maintenance for aircraft and risk prediction at The Bill and Melinda Gates Foundation.
Bio: Dr. Paul Hofmann is an expert in AI, computer simulations and graphics. He is CTO of Saffron Technology, a Big Data predictive analytics firm named top 5 coolest vendors in Enterprise Information Management by Gartner. Before joining Saffron, Paul was VP of Research at SAP Labs in Silicon Valley. He has authored two books and numerous publications. Paul received his Ph.D. in Physics at the Darmstadt University of Technology.
Our format is flexible: We usually have speakers who talk for ~30 minutes each and then do Q+A, plus discussion.
There'll be beer afterwards, of course!
c/o WhitePages (http://maps.google.com/maps?q=1301+5th+Avenue+%231700%2C+Seattle%2C+WA),[masked]th Avenue, 3rd Floor "conference center" Seattle, WA
Doors open 30 minutes ahead of show-time. Please show up at least 15 minutes early out of respect for our first speaker.