Lovely ppt from the formidable Jeffrey Bean, whose lucid style in explaining R has made me a big fan of his awesome work!
Some slides I liked on cloud computing infrastructure as offered by Amazon, IBM, Google , Windows and Oracle
I really liked the initiatives at JMP/Academic. Not only they offer the software bundled with a textbook, which is both good common sense as well as business sense given how fast students can get confused
(Rant 1 Bundling with textbooks is something I think is Revolution Analytics should think of doing instead of just offering the academic version for free downloading- it would be interesting to see the penetration of R academic market with Revolution’s version and the open source version with the existing strategy)
From http://www.jmp.com/academic/textbooks.shtml
Major publishers of introductory statistics textbooks offer a 12-month license to JMP Student Edition, a streamlined version of JMP, with their textbooks.
and a glance through this http://www.jmp.com/academic/pdf/jmp_se_comparison.pdf shows it is a credible and not extremely whittled down version which would be just dishonest.
And I loved this Reference Card at http://www.jmp.com/academic/pdf/jmp10_se_quick_guide.pdf
Oracle, SAP- Hana, Revolution Analytics and even SAS/STAT itself can make more reference cards like this- elegant solutions for students and new learners!
More- creative-rants Honestly why do corporate sites use PDFs anymore when they can use Instapaper , or any of these SlideShare/Scribd formats to show information in a better way without diverting the user from the main webpage.
But I digress, back to JMP
Resources for Faculty Using JMP® Student Edition
Faculty who select a JMP Student Edition bundle for their courses may be eligible for additional resources, including course materials and training.
Special JMP® Student Edition for AP Statistics
JMP Student Edition is available in a convenient five-year license for qualified Advanced Placement statistics programs.
Try and have a look yourself at http://www.jmp.com/academic/student.shtml
From http://en.wikipedia.org/wiki/3D_printing
Additive manufacturing or 3D printing[1] is a process of making three dimensional solid objects from a digital model. 3D printing is achieved using additive processes, where an object is created by laying down successive layers of material.[2] 3D printing is considered distinct from traditional machining techniques (subtractive processes) which mostly rely on the removal of material by drilling, cutting etc.
A world without factories , or atleast not as many. Where the only thing to be bought is design and raw material . Direct from the creators to the consumers.
Imagine 2025 – with the latest generation of 3 D printers. You browse though online catalogs, select designs for furniture, accessories, clothes. Click buy and then print.
No more inventory planning ( except for the raw material wood,synthetic,cloth, plastic or better still an intermediate that can be done in all of these). Everything is bio-degradable in this new world of 3D printers.
That future is closer than you think! No more Made in China vs Made in USA
Everything will be made at home! designed by artists! delivered by Internet.
This is probably how they will shift manufacturing back to the rest of the planet to the First World, as both China and India are lagging behind in understanding the ramifications of mass produced 3D printers. 3D printers could do to factories what automatic washing machines did to laundry.
from http://www.sas.com/events/analytics/us/index.html
SAS and more than 1,000 analytics experts gather at
Caesars Palace
Pre-Conference Workshops – Oct 7
Conference – Oct 8-9
Post-Conference Training – Oct 10-12
Caesars Palace, Las Vegas
The following are confirmed keynote speakers for Analytics 2012. 
Since he co-founded SAS in 1976, Jim Goodnight has served as the company’s Chief Executive Officer.
Dr. William Hakes is the CEO and co-founder of Link Analytics, an analytical technology company focused on mobile, energy and government verticals.
Tim Rey has written over 100 internal papers, published 21 external papers, and delivered numerous keynote presentations and technical talks at various quantitative methods forums. Recently he has co-chaired both forecasting and data mining conferences. He is currently in the process of co-writing a book, Applied Data Mining for Forecasting.
http://www.sas.com/events/analytics/us/train.html
Plan to come to Analytics 2012 a day early and participate in one of the pre-conference workshops or take a SAS Certification exam. Prices for all of the preconference workshops, except for SAS Sentiment Analysis Studio: Introduction to Building Models and the Business Analytics Consulting Workshops, are included in the conference package pricing. You will be prompted to select your pre-conference training options when you register.
This course provides an introduction to SAS Sentiment Analysis Studio. It is designed for system designers, developers, analytical consultants and managers who want to understand techniques and approaches for identifying sentiment in textual documents.
View outline
Sunday, Oct. 7, 8:30a.m.-12p.m. – $250
This workshop is designed for the analyst, statistician, or executive who wants to discuss best-practice approaches to solving specific business problems, in the context of analytics. The two-hour workshop will be customized to discuss your specific analytical needs and will be designed as a one-on-one session for you, including up to five individuals within your company sharing your analytical goal. This workshop is specifically geared for an expert tasked with solving a critical business problem who needs consultation for developing the analytical approach required. The workshop can be customized to meet your needs, from a deep-dive into modeling methods to a strategic plan for analytic initiatives. In addition to the two hours at the conference location, this workshop includes some advanced consulting time over the phone, making it a valuable investment at a bargain price.
View outline
Sunday, Oct. 7; 1-3 p.m. or 3:30-5:30 p.m. – $200
This half-day lecture teaches students how to integrate demand-driven forecasting into the consensus forecasting process and how to make the current demand forecasting process more demand-driven.
View outline
Sunday, Oct. 7; 1-5 p.m.
Forecast Value Added (FVA) is the change in a forecasting performance metric (such as MAPE or bias) that can be attributed to a particular step or participant in the forecasting process. FVA analysis is used to identify those process activities that are failing to make the forecast any better (or might even be making it worse). This course provides step-by-step guidelines for conducting FVA analysis – to identify and eliminate the waste, inefficiency, and worst practices from your forecasting process. The result can be better forecasts, with fewer resources and less management time spent on forecasting.
View outline
Sunday, Oct. 7; 1-5 p.m.
This course gives an introduction to methods of unstructured data analysis, document classification and document content identification. The course also uses examples as the basis for constructing parse expressions and resulting entities.
View outline
Sunday, Oct. 7; 1-5 p.m.
This course serves as an introduction to data mining and SAS Enterprise Miner for Desktop software. It is designed for data analysts and qualitative experts as well as those with less of a technical background who want a general understanding of data mining.
View outline
Sunday, Oct. 7, 1-5 p.m.
This half-day lecture teaches students how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the unobserved components models (UCM). This course is designed for business analysts who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques.
View outline
Sunday, Oct. 7, 1-5 p.m.
This seminar will provide a brief introduction to the use of SAS Enterprise Guide for graphical and data analysis. However, the focus will be on using SAS Enterprise Guide and SAS Enterprise Miner along with the Rapid Predictive Modeling component to build predictive models. Predictive modeling will be introduced using the SEMMA process developed with the introduction of SAS Enterprise Miner. Several examples will be used to illustrate the use of the Rapid Predictive Modeling component, and interpretations of the model results will be provided.
View outline
Sunday, Oct. 7, 1-5 p.m
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A nice geeky function in Rapid Miner is the Obfuscator
This operator can be used to anonymize your data. It is possible to save the obfuscating map into a fi le which can be used to remap the old values and names. Please use the operator Deobfuscator for this
RapidMiner is free for download here (its open source)
DECISION STATS 