Paul / Trent,
THX guys for those responses. Actually, I was thinking more in the
direction of
Business
Intelligence, or
Web Site
Scraping. The direction I am going in is to find something
out there, versus parse data, on an existing data base. If, that
makes sense to the both of you. Or, do I have it all wrong here?
The project I am working on is to find possible candidates, with a
European partner, for the bolt-on acquisition of a certain type of
Biotech company. He ran a NASDAQ listed company, and I worked
directly for him. We've run the gamut, of our global contacts, and
are looking to dig deeper. That, at several levels.
To be honest, we always relied up IT, but probably never asked the
right questions. Or, vice versa. See the conundrum here?
If you've got any other ideas, please do get back to me. I've been
running Linux forever. The reason was simple. I got tired of
playing M$ S/W Engineer, and being asked, in Taiwan, or other
countries, to insert my original M$ CD. LOL!
THX again for your time!
John
On 09/09/2014 12:38 AM, Paul Mooring wrote:
R definitely is the standard currently, but I would
add Julia to the list of notable languages for data science.
Also while it's much less popular, I've played with Incanter (a
statistics/data science library for clojure) a bit and found it
delightful. My experience with Incanter does come with the
disclaimer that I've never needed to work with "big data", no
need for hadoop/map reduce and also I like lisps a good bit and
that probably colors how anyone would feel about working with
clojure vs working with R.
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