Tag Archives: Revolution Analytics

Distributed Analytics: A Primer

Can we leverage distributed computing for machine learning and predictive analytics? The question keeps surfacing in different contexts, so I thought I’d take a few minutes to write an overview of the topic. The question is important for four reasons: Source data for analytics frequently resides in distributed data platforms, such as MPP appliances or Hadoop; In many cases, the

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Smart Money: Venture Capital for Analytics 2013

Thanks to Crunchbase’s downloadable database, we can report that in 2013 investors poured more than $2 billion into Analytic startups, up 38% from 2012.  Crunchbase reports 2013 funding for Analytics ventures more than five times greater than in 2009. Palantir led the pack in new funding, going to the well twice, in October and December, to raise a total of $304m

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Strata Report: Advanced Analytics in Hadoop

Here is a quick review of the capabilities for advanced analytics in Hadoop for five vendors at the recent Strata NYC conference: 0xData Alpine Data Labs Oracle SAS Skytree 0XData Product(s) H20 (open source project) h2o (R package) Description Smart people from Stanford with VC backing and a social media program.   Services business model with open source software.  H20 is an

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SAS Analyst Conference: Take Two

Analyst comments about SAS’ 24th annual analyst conference continue to dribble out.   Ordinarily, events like this produce a storm of Google alerts, but this year the quiet speaks volumes.   Yesterday, Tony Cosentino of Ventana Research published his perspective on the conference, writing at length about SAS Visual Analytics; link here. Here are a few quotes from Mr. Cosentino’s

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Notes From #BigDataMN

Analytics conferences tend to be held in places like Orlando or Las Vegas, where it’s sunny and warm all of the time and there are copious incidental pleasures to fill the off hours.  I can’t speak to the incidental pleasures of Minneapolis in January, but warm it is not; peak temperature on Monday had a minus sign in front of

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RevoScaleR Beats SAS, Hadoop for Regression on Large Dataset

Still catching up on news from Strata conference. This post from Revolution Analytics’ blog summarizes an excellent paper jointly presented at Strata by Allstate and Revolution Analytics. The paper documents how a team at Allstate struggled to run predictive models with SAS on a data set of 150 million records.  The team then attempted to run the same analysis using

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Embrace Open Source Analytics

Suppose you could implement an analytics platform with comprehensive out-of-the-box capabilities, a flexible programming environment, good visualization capabilities and a growing body of skilled users.  Suppose this platform leveraged a massively parallel architecture for high performance and scalability.  And suppose you could do this without investing in software fees. You don’t have to suppose, because IBM Netezza helps you leverage

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