Proton is a name of a project in which have investigated the proactive event-driven approach (see our talk in DEBS'2012). I came across another proton, this time from UC Berkeley. It deals with codifying gestures as regular expressions of touch event symbols. In the website you can find tutorial, downloadable version and papers. Interesting idea, enjoy!
This is a blog describing some thoughts about issues related to event processing and thoughts related to my current role. It is written by Opher Etzion and reflects the author's own opinions
Thursday, October 11, 2012
Wednesday, October 10, 2012
SAS announcement on event processing
SAS announced today that a new "SAS DataFlux Event Stream Processing Engine" will be available in December. It is described as: "the new software is a form of complex event processing (CEP) technology...incorporates relational, procedural and pattern-matching analysis of structured and unstructured data". Welcome to the event processing club, this seems to be an indication that the analytics guys see the value of adding event processing to their portfolio, I guess that either the "limited appeal" of event processing has somewhat changed in the last couple of years to justify it. Anyway - I welcome SAS to the club, and hope that they will also become active part of the event processing community.
Sunday, October 7, 2012
On big data, small things and events that matter
In a recent post in the Harvard Business Review Blog entitled: "Big Data Doesn't Work if You Ignore the Small Things that Matter" , Robert Plant argues that in some cases organization invest a lot in "big data" projects trying to get insights around their strategy, while failing to notice the small things, like customers leaving due to bad service. Indeed big data and analytics are now fashionable and somewhat over-hyped. There is also some belief, fueled by the buzz that it solves all the problems of the universe, as argued by Sethu Raman in his DEBS'12 keynote address. Events are playing both in the big data game, but also in the small data game, trying to observe a current happening, such as time-out on service, long queues etc..., when it relates to service, and other phenomena in other domains. Sometimes the small things are the most critical.
I'll write more about big data and statistical reasoning in a subsequent post.
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