At my firm we have been calculating fundamental stock factors each week for over a decade. We have the performance of each of these factors. I'd like to enhance the statistical analysis of these factors and improve the multi-factor optimization. Is there a somewhat beginner "popular" software that interfaces with a sql database that would help me to perform this analysis? I understand this is probably a very elementary question here, thank you for your time.
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All major statistics packages like R, Stata, and SAS can easily execute SQL queries and pull data from an SQL database for analysis via an ODBC connection (and insert it as well).
Some, like SAS and special enterprise flavors of R, can actually run in the database, which is more convenient for using estimation results to do something automated or if you're crunching new big data all the time. That way you can avoid having to port the analysis results to another application and downloading tons of data.
The first is trivial to set up, and the second is more involved. The right choice depends on your DB setup, how much data you need, and what you plan to do with the results of the analysis, as well as cost.

dimitriy
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I use R's `RODBC` all the time. Highly recommend. http://cran.r-project.org/web/packages/RODBC/RODBC.pdf – AdamO May 10 '13 at 21:16
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I would take a serious look at Stata. It is certainly beginner-friendly in that it has a GUI for many of the built-in commands, but the GUI also spits out the actual code so that you can progress to Jedi levels. It also has excellent pdf documentation. – dimitriy May 10 '13 at 21:39
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Ordinary non-enterprise R does this too, e.g. The `dbplyr` extension to `dplyr` allows you to formulate your query in (tidy) R as if your database tables were local data frames, translates it into SQL and returns the results as another data frame. It's remarkably smooth in my experience, particularly if you find ODBC annoying and don't care to write the SQL yourself. (`dbplyr` will tell you what SQL it wrote for you, if you care to start though). – conjugateprior Feb 04 '18 at 20:32