Intel has a long history using SAS and its visualization front-end JMP.
Both of those products now support augmentation with the open source R language.
So prototyping the analytics needed to support Hadoop cloud technology is probably underway using SAS/JMP and R. But there is much more open source software that emulates the MATLAB engineering math tools, which are probably a second part of the mix. I am sure that by now (Its already 11 days since this article was posted) there must be many more web postings on the big data analytics open source catalog of tools and even the likely need of GUI's to supported them in office world. So how about another update on that catalog and perhaps current global usage trends? Machine learning algorithms, for example, used by everyone from engineers to marketers and economists could be found in open source. Many big data blogs are hyping all of these open source tools. Somebody needs to mine those blogs, talk to Intel, and forecast some scenarios for "the rest of us." You might be just that forecaster.
Replay available now: A handful of emerging network technologies are competing to be the preferred wide-area connection for the Internet of Things. All claim lower costs and power use than cellular but none have wide deployment yet. Listen in as proponents of leading contenders make their case to be the metro or national IoT network of the future. Rick Merritt, EE Times Silicon Valley Bureau Chief, moderators this discussion. Join in and ask his guests questions.