Greetings all,

This isn't a request for help, but I thought the following article from the
New York Times would be of interest to you all.

Enjoy!

Adam



*Data Analysts Captivated by R's Power*
By ASHLEE VANCE
Published ONLINE: January 6, 2009
URL:
http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html
A version of this article appeared in print edition on January 7, 2009, on
page B6

R is also the name of a popular programming language used by a growing
number of data analysts inside corporations and academia. It is becoming
their lingua franca partly because data mining has entered a golden age,
whether being used to set ad prices, find new drugs more quickly or
fine-tune financial models. Companies as diverse as Google, Pfizer, Merck,
Bank of America, the InterContinental Hotels Group and Shell use it.

But R has also quickly found a following because statisticians, engineers
and scientists without computer programming skills find it easy to use.

"R is really important to the point that it's hard to overvalue it," said
Daryl Pregibon, a research scientist at Google, which uses the software
widely. "It allows statisticians to do very intricate and complicated
analyses without knowing the blood and guts of computing systems."

It is also free. R is an open-source program, and its popularity reflects a
shift in the type of software used inside corporations. Open-source software
is free for anyone to use and modify. I.B.M., Hewlett-Packard and Dell make
billions of dollars a year selling servers that run the open-source Linux
operating system, which competes with Windows from Microsoft. Most Web sites
are displayed using an open-source application called Apache, and companies
increasingly rely on the open-source MySQL database to store their critical
information. Many people view the end results of all this technology via the
Firefox Web browser, also open-source software.

R is similar to other programming languages, like C, Java and Perl, in that
it helps people perform a wide variety of computing tasks by giving them
access to various commands. For statisticians, however, R is particularly
useful because it contains a number of built-in mechanisms for organizing
data, running calculations on the information and creating graphical
representations of data sets.

Some people familiar with R describe it as a supercharged version of
Microsoft's Excel spreadsheet software that can help illuminate data trends
more clearly than is possible by entering information into rows and columns.

What makes R so useful — and helps explain its quick acceptance — is that
statisticians, engineers and scientists can improve the software's code or
write variations for specific tasks. Packages written for R add advanced
algorithms, colored and textured graphs and mining techniques to dig deeper
into databases.

Close to 1,600 different packages reside on just one of the many Web sites
devoted to R, and the number of packages has grown exponentially. One
package, called BiodiversityR, offers a graphical interface aimed at making
calculations of environmental trends easier.

Another package, called Emu, analyzes speech patterns, while GenABEL is used
to study the human genome.

The financial services community has demonstrated a particular affinity for
R; dozens of packages exist for derivatives analysis alone.

"The great beauty of R is that you can modify it to do all sorts of things,"
said Hal Varian, chief economist at Google. "And you have a lot of
prepackaged stuff that's already available, so you're standing on the
shoulders of giants."

R first appeared in 1996, when the statistics professors Ross Ihaka and
Robert Gentleman of the Universityof Auckland in New Zealand released the
code as a free software package.

According to them, the notion of devising something like R sprang up during
a hallway conversation. They both wanted technology better suited for their
statistics students, who needed to analyze data and produce graphical models
of the information. Most comparable software had been designed by computer
scientists and proved hard to use.

Lacking deep computer science training, the professors considered their
coding efforts more of an academic game than anything else. Nonetheless,
starting in about 1991, they worked on R full time. "We were pretty much
inseparable for five or six years," Mr. Gentleman said. "One person would do
the typing and one person would do the thinking."

Some statisticians who took an early look at the software considered it
rough around the edges. But despite its shortcomings, R immediately gained a
following with people who saw the possibilities in customizing the free
software.

John M. Chambers, a former Bell Labs researcher who is now a consulting
professor of statistics at StanfordUniversity, was an early champion. At
Bell Labs, Mr. Chambers had helped develop S, another statistics software
project, which was meant to give researchers of all stripes an accessible
data analysis tool. It was, however, not an open-source project.

The software failed to generate broad interest and ultimately the rights to
S ended up in the hands of Tibco Software. Now R is surpassing what Mr.
Chambers had imagined possible with S.

"The diversity and excitement around what all of these people are doing is
great," Mr. Chambers said

While it is difficult to calculate exactly how many people use R, those most
familiar with the software estimate that close to 250,000 people work with
it regularly. The popularity of R at universities could threaten SAS
Institute, the privately held business software company that specializes in
data analysis software. SAS, with more than $2 billion in annual revenue,
has been the preferred tool of scholars and corporate managers.

"R has really become the second language for people coming out of grad
school now, and there's an amazing amount of code being written for it,"
said Max Kuhn, associate director of nonclinical statistics at Pfizer. "You
can look on the SAS message boards and see there is a proportional downturn
in traffic."

SAS says it has noticed R's rising popularity at universities, despite
educational discounts on its own software, but it dismisses the technology
as being of interest to a limited set of people working on very hard tasks.

"I think it addresses a niche market for high-end data analysts that want
free, readily available code," said Anne H. Milley, director of technology
product marketing at SAS. She adds, "We have customers who build engines for
aircraft. I am happy they are not using freeware when I get on a jet."

But while SAS plays down R's corporate appeal, companies like Google and
Pfizer say they use the software for just about anything they can. Google,
for example, taps R for help understanding trends in ad pricing and for
illuminating patterns in the search data it collects. Pfizer has created
customized packages for R to let its scientists manipulate their own data
during nonclinical drug studies rather than send the information off to a
statistician.

The co-creators of R express satisfaction that such companies profit from
the fruits of their labor and that of hundreds of volunteers.

Mr. Ihaka continues to teach statistics at the University of Auckland and
wants to create more advanced software. Mr. Gentleman is applying R-based
software, called Bioconductor, in work he is doing on computational biology
at the Fred Hutchinson Cancer Research Center in Seattle.

"R is a real demonstration of the power of collaboration, and I don't think
you could construct something like this any other way," Mr. Ihaka said. "We
could have chosen to be commercial, and we would have sold five copies of
the software."

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