Tag Archives: Open Source

Disruption: It’s All About the Business Model

This post is an excerpt adapted from my book, Disruptive Analytics, available soon from Apress and Amazon. (Note: under my contract with Apress I am legally obligated to link to their site, but it’s not yet possible to order the book there. Use the Amazon link if you want the book.) The analytics business is booming. Technology consultant IDC estimates total

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Gartner Advanced Analytics Magic Quadrant 2015

Gartner’s latest Magic Quadrant for Advanced Analytics is out; for reference, the 2014 report is here; analysis from Doug Henschen here.  Key changes from last year: Revolution Analytics moves from Visionary to Niche Alpine and Microsoft move from Niche to Visionary Oracle, Actuate and Megaputer drop out of the analysis Gartner changed its evaluation criteria this year to reflect only “native”

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Microsoft Buys Revolution Analytics

On Friday, January 23, Microsoft announced an agreement to acquire Revolution Analytics.  Coverage of the announcement in the media is extensive, with stories by TechCrunch, Wired, ZDNet, VentureBeat and many others (here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here, here and here.) Microsoft did not disclose the negotiated purchase price; Revolution’s total capitalization

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Python for Analytics

A reader complains that I did not include Python in a survey of Machine Learning in Hadoop.  It’s a fair point.  There was a lively debate last year between R and Python advocates, variously described as a war or a boxing match.  Matt Asay argued that Python is displacing R; Sharon Machlis and David Smith countered.  In this post I review the

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Apache Spark for Big Analytics (Updated for Spark Summit and Release 1.0.1)

Updated and bumped July 10, 2014. For a powerpoint version on Slideshare, go here. Introduction Apache Spark is an open source distributed computing framework for advanced analytics in Hadoop.  Originally developed as a research project at UC Berkeley’s AMPLab, the project achieved incubator status in Apache in June 2013 and top-level status in February 2014.  According to one analyst, Apache Spark is among the five

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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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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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