Haydn Shaughnessy at The Forbes blog provides a list of the "Top 20 Influencers in Big Data", and I'm humbled to report that yours truly is listed there at #2. It's an instantaneous ranking based on the social-media tracking tool Traakr, but it's still great to be listed alongside writers for SiliconAngle, GigaOM, and...
Posts Tagged ‘ Big Data ’
Norman Nie on two big problems with Big Data
Revolution Analytics CEO Norman Nie sat down with Cassimir Medford from Business Agility to talk about the problems business today face with respect to Big Data. The two big problems identified: finding adequately trained personnel and locating the right tools. Norman traces the problem of finding skilled practitioners to work with Big Data to...
EMC survey differentiates BI and Data Science
EMC last week published the results of a survey of 462 IT decision makers who self-identified as either a data scientist or business intelligence professional (plus 35 invitees who were attendees at the EMC Data Scientist Summity and/or Kaggle competitors). There's a nice summary of the conclusions at the EMC blog, (where data scientists...
RHadoop update: new tools for Hadoop map-reduce tasks in R
The open-source RHadoop project to integrate R and Hadoop continues apace, with a new version of the rmr package released this week. Changes in this version improve performance when storing and retrieving R objects from Hadoop with a native serialization process, support for equijoins (a MapReduce-style merge) and some new higher-level R functions to...
Why we need to deal with big data in R
Responding to the birth rates analysis in the post earlier this week on big-data analysis with Revolution R Enterprise, Luis Apiolaza asks at the Quantum Forests blog, do we really need to deal with big data in R? My basic question is why would I want to deal with all those 100 million records...
Analyzing birth rates from census data from RevoScaleR
In yesterday's webinar, "New Features in Revolution R Enterprise 5.0 to Support Scalable Data Analysis", Sue Ranney demonstrated the features of the RevoScaleR big data analysis package included with Revolution R Enterprise. In the webinar, she showed how to use the rxImport function to import big data sets from SAS, SPSS or ODBC, how...
Webinar Tomorrow: What’s new in Revolution R Enterprise 5.0
A reminder that Sue Ranney will be presenting the webinar New Features in Revolution R Enterprise 5.0 (Including RevoScaleR) to support Scalable Data Analysis tomorrow (Thursday) at 11AM Pacific time. To whet your appetite, here's another video demonstation of more of the new big data analysis features, including the rxDataStep function to preprocess a...
Announcing Revolution R Enterprise 5.0
We're proud to announce the latest update to the enhanced, commercial-grade distribution of R, Revolution R Enterprise 5.0. With each new release, Revolution R Enterprise adds more capabilities to open-source R, to make R users more productive, to improve performance of R programs, to support Big Data analytics, and to provide servers and APIs...
The Marriage of Hadoop and R: Revolution Analytics at Hadoop World
Revolution Analytics CTO David Champagne visited Hadoop World 2011 this week, and delivered a presentation on "The Powerful Marriage of R and Hadoop" to a standing-room-only crowd of R and Hadoop enthusiasts. I've included David's slides below: The talk also generated praise on Twitter, for example: David was also interviewed by The Cube during...
Webinar Nov 17: What’s new in Revolution R Enterprise 5.0
Revolution R Enterprise 5.0 will be released soon, and Sue Ranney, VP of Development at Revolution Analytics, will host a webinar on Thursday November 17 to get you up to speed on the latest features: Revolution R Enterprise 5.0 is Revolution Analytics’ scalable analytics platform. At its core is Revolution Analytics’ enhanced Distribution of...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).