Tag: Analytics

SAS X

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Tal G, creator of the rbloggers.com website, has created a new blog aggregator for SAS language users at http://sas-x.com/

With almost 26 blogs joining there (I suspect many more should join , it seems like a good website to use for analytics users and students.  My favorite SAS Blog is http://statcompute.spaces.live.com/ – its pure code- little anything else.

Related-

SAS MACRO TO CALCULATE PDO (Points to Double Odds) OF A SCORECARD

A SAS MACRO FOR DECISION STUMP

A DEMO OF VECTOR AUTOREGRESSIVE FORECASTING MODEL

 

 

 

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R is Ready for Business™

A new 5 page brochure from Revolution Analytics. Not that slick and some marketing under-kill (which frankly is a surprise)- but I guess Revolution Analytics does not have a full time graphics designer to help with it’s collateral.

Take a look if you are curious how and why R is getting more and more ready for business.

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An Introduction to Data Mining-online book

I was reading David Smith’s blog http://blog.revolutionanalytics.com/

where he mentioned this interview of Norman Nie, at TDWI

http://tdwi.org/Articles/2010/11/17/R-101.aspx?Page=2–

where I saw this link (its great if you want to study Data Mining btw)

http://www.kdnuggets.com/education/usa-canada.html –

and I c/liked the U Toronto link

http://chem-eng.utoronto.ca/~datamining/

Best of All- I really liked this online book created by Professor S. Sayad

Its succinct and beautiful and describes all of the Data Mining you want to read in one Map (actually 4 images painstakingly assembled with perfection)

The best thing is- in the original map- even the sub items are click-able for specifics like Pie Chart and Stacked Column chart are not in one simple drop down like Charts- but rather by nature of the kind of variables that lead to these charts. For doing that- you would need to go to the site itself- ( see http://chem-eng.utoronto.ca/~datamining/dmc/categorical_variables.htm

vs

http://chem-eng.utoronto.ca/~datamining/dmc/categorical_numerical.htm

Again- there is no mention of the data visualization software used to create the images but I think I can take a hint from the Software Page which says software used are-

Software

See it on your own-online book (c)Professor S. Sayad

Really good DIY tutorial

http://chem-eng.utoronto.ca/~datamining/dmc/data_mining_map.htm

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Gartner BI and Inf Mgmt Summit 2011- 30 min One on Ones

From the land Down Under, where Gartner gathers business summit thunder.

http://www.gartner.com/technology/summits/apac/business-intelligence/index.jsp

Gartner Business Intelligence
& Information Management Summit 2011

February 22 – 23 • Sydney, AUSTRALIA
gartner.com/ap/bi

 Register Now

From Information to Intelligence:

Evaluate, Execute and Evolve

At Gartner Business Intelligence & Information Management Summit 2011 you will experience a unique mix of Gartner research presentations, guest keynote addresses, real-life case studies and interactive panel discussions to provide you with a holistic view of the business intelligence and performance management landscape. Information, insight and advice are channeled through an increasingly targeted and focused approach, taking you from the high-level strategic view all the way to your specific issue.

Click here to view the full agenda or download the brochure.

AGENDA HIGHLIGHTS

teamsend


Guest Keynote Address
Future Thinking – Global Trends and Thinking that are Upending your Business

Anders Sorman-Nilsson
Creative Director, Thinque

Click here to read more about this session.

Best Practice Workshops:

  • How to Become an Effective Data Warehouse Modeler
  • Analytics – Business Intelligence and Performance Management ITScore

Analyst User Roundtables:

  • Enterprise Information Management – Focusing on What Matters to the Business
  • Sharepoint – thin edge of the wedge to the MS family
  • Preparing for the 2020 workplace

Worldwide Expertise at Your Fingertips!
Your questions on Business Intelligence and Performance Management answered. Meet the Gartner Analysts presenting at the Summit and book your exclusive 30 minute one-on-one ( lap top dance) with the Analysts of your choice.

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AsterData partners with Tableau

This chart represents several constituent comp...
Image via Wikipedia

Tableau which has been making waves recntly with its great new data visualization tool announced a partner with my old friends at AsterData. Its really cool piece of data vis and very very fast on the desktop- so I can imagine what speed it can help with AsterData’s MPP Row and Column Zingbang AND Parallel Analytical Functions

Tableau and AsterData also share the common Stanfordian connection (but it seems software is divided quite equally between Stanford, Hardvard Dropouts and North Carolina )

It remains to be seen in this announcement how much each company  can leverage the partnership or whether it turns like the SAS Institute- AsterData partnership last year or whether it is just to announce connectors in their software to talk to each other.

See a Tableau vis at

http://public.tableausoftware.com/views/geographyofdiabetes/Dashboard2?:embed=yes&:toolbar=yes

AsterData remains the guys with the potential but I would be wrong to say MapReduce–SQL is as hot in December 2010 as it was in June 2009- and the elephant in the room would be Hadoop. That and Google’s continued shyness from encashing its principal comptency of handling Big Data (but hush – I signed a NDA with the Google Prediction API– so things maaaay change very rapidly on ahem that cloud)

Disclaimer- AsterData was my internship sponsor during my winter training while at Univ of  Tenn.

 

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PAWCON Bay Area March

The biggest Predictive Analytics Conference comes back to the SF Bay in March next year.

From

http://www.predictiveanalyticsworld.com/sanfrancisco/2011/

Predictive Analytics World March 2011 in San Francisco is packed with the top predictive analytics experts, practitioners, authors and business thought leaders, including keynote speakers:


Sugato Basu, Ph.D.
Senior Research Scientist
Google
Lessons Learned in Predictive Modeling 
for Ad Targeting
Eric Siegel, Ph.D.
Conference Chair
Predictive Analytics World
Five Ways Predictive Analytics
Cuts Enterprise Risk



Plus special plenary sessions from industry heavy-weights:


Andreas S. Weigend, Ph.D.
weigend.com
Former Chief Scientist, Amazon.com
The State of the Social Data Revoltion
John F. Elder, Ph.D.
CEO and Founder
Elder Research
Data Mining Lessons Learned



Predictive Analytics World focuses on concrete examples of deployed predictive analytics. Hear from the horse’s mouth precisely how Fortune 500 analytics competitors and other top practitioners deploy predictive modeling, and what kind of business impact it delivers. Click here to view the agenda at-a-glance.

PAW SF 2011 will feature speakers with case studies from leading enterprises. such as:

PAW’s March agenda covers hot topics and advanced methods such as uplift (net lift) modeling, ensemble models, social data, search marketing, crowdsourcing, blackbox trading, fraud detection, risk management, survey analysis and otherinnovative applications that benefit organizations in new and creative ways.

Join PAW and access the best keynotes, sessions, workshops, exposition, expert panel, live demos, networking coffee breaks, reception, birds-of-a-feather lunches, brand-name enterprise leaders, and industry heavyweights in the business.

 

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Using SAS/IML with R

Analyze That
Image via Wikipedia

SAS just released an updated documentation to SAS/IML language with a special chapter devoted to using R

Here is an example-

CALL EXPORTMATRIXTOR( IMLMatrix, RMatrix ) ;

CALL IMPORTMATRIXFROMR( IMLMatrix, RExpr ) ;

If you have existing SAS licences and existing hardware and loots of data -this may be the best of both worlds- without getting into the mess of technically learning MKL threads/BLAS/Premium Packages/Cloud

Another thought- its a good professional looking help book, which is what more R packages can do (work on improving ease of their help/update vignettes)

 

Link-http://support.sas.com/documentation/cdl/en/imlug/63541/HTML/default/viewer.htm#r_toc.htm

 

Calling Functions in the R Language

[continuerule]

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