Last week Hass, Mark, and myself attended the Internet of Things World Conference in Santa Clara, California. Attendees came from all over the world to learn, share and discuss the Internet of Things (IoT). It was four days jam packed with workshops, keynote speeches, breakout sessions and vendor exhibits. We spent the first day in a workshop discussing both the technology and business behind the Internet of Things. Our next three days were spent selecting and attending various talks about everything IoT. Between sessions we would hit up the showroom floor to visit vendor booths and view live demos. We learned a great deal of information, so I am going to try to impart some of that knowledge by sharing some of the key points from the conference.
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Welcome to the first installment of a series of Q&A blog posts. My name is Daniela Williams, Project Manager at ISE, and I'll be asking ISE team members questions to help give insight into what makes us tick.
First up is our website cover model, Matt Coventon (yep, all the people in our website photos are actual team members). Matt is a Senior Engineer and the practice lead for the Big Data professional service. So sit back, learn a bit about Big Data, and get a sneak peek at Matt's presentation at the In-Memory Computing Summit comingup on May 23rd-24th.
One problem with the Big Data paradigm is the lack of Big Data capable software engineers. Why is this? Let's check off the reasons:
- It is hard to reason about parallel computation. Steve Jobs was famous for saying that "nobody knows how to program [multi-core]. I mean two, yeah; four, not really; eight, forget it." Now take those eight cores and multiply it across tens, hundreds, or in some cases, thousands of machines. This is a difficult problem.
- There is a constantly changing ecosystem of tools, languages, and work flows. This leads to confusion among newcomers on which to learn and use, and which are irrelevant.