The Ohri Framework - Data Mining on
Demand<http://decisionstats.com/2008/the-ohri-framework-data-mining-on-demand/>


Part of the reason SAS continues to enjoy a profitable lead is

1) Standardized language elements (Data and Procs)

2)Ease of Learning SAS

3) Output Delivery to multiple sources

4) Input from multiple data sources

But the most important reason is the sheer efficiency of the PDV in reading
large files . If Excel could load a 300 mb file that easily, it would make a
significant dent.Large files are assumed to be used by larger license
holders.

Cloud computing could be of help here to languages like R. R is very very
good in advanced stats, is free, the packages are peer reviewed. It has
little known but very good GUI's too (like rattle). If you place rattle GUI
in a cloud , it would use processing power on demand, and output results.SAS
wont do it because they charge by the CPU count on this, and thats an idle
asset (reaping rewards from programming done long back)

Thus you save on hardware costs and software costs.People pay only when they
use the system. But an additional costs is fixed cost of the remote
application built to support the framework, including transport bandwidth
cost. A sugestion could be to use 1_compressed and encrypted data transfers
to and fro from the remote cloud.PGP.com would be of help here

Pay for bandwidth, and cost + small markup for the cloud hosting costs.
Economies of scale will ensue.

R's graphical system is superior than than SAS, but it can be tweaked to
newer graphical softwares like Silverlight.

The little guy no longer needs to squeeze himself for the big computing
power.

I could be totally wrong here, but it may be worth a shot.

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