Open Source replacements for Operations Research and Analytics Software

I was reading an article from Datamation on 70 Open Source Replacements for Small Business when I noticed a glaring omission.  Where are the software applications for Operations Research and Analytics?  So here is my best addendum to this article that should complete what small business should know about Open Source analytics productivity software.

Statistics and Computation

1.  R Project

Replaces: SAS, SPSS

R is a free and open source statistical computing environment that holds its own against some of the most established proprietary statistical environments.  R is available on all operating systems and is free for download.  R also has a community driven library of add-on packages that are also freely available and cover almost any statistical, mathematical, or optimization need.

Also a great reference manual for those switching from SAS to R is SAS and R: Data Management, Statistical Analysis, and Graphics




2.  RapidMiner

Replaces:  KnowledgeSEEKER

RapidMiner is a data mining software with a graphical front-end.  RapidMiner is suitable for most data mining and data transformation needs.


Mathematical Programming and Optimization

3.  GLPK

Replaces:  AMPL

GLPK is a GNU/free software linear programming software kit.  GLPK is intended for large-scale linear programming, mixed integer programming.  GLPK is based on GNU MathProg (or GMPL) which is considered a subset of the AMPL syntax.  GLPK also has its own solver.

4.  Symphony

Replaces: CPLEX, Gurobi

Symphony is a mixed integer linear programming solver developed under COIN-OR.  Symphony is a flexible framework that offers many methods to customize solver capabilities given problem sets.


5.  OpenSolver

Replaces:  Excel Solver

OpenSolver is a linear an integer optimizer alternative to the Excel Solver in Microsoft Excel.  OpenSolver is based on the COIN-OR CBC engine.  Unlike the Excel Solver there is no software limits to the size of the problem that can be solved.

OReilly - Quiet Rise of Machine Learning

An interesting article from the OReilly Radar blog by Jenn Webb on the Quiet Rise of Machine Learning.  I love the insight from the article that decision sciences like Operations Research are getting more mainstream.  Machine Learning is that one science of mixing data mining and predictive analytics.  The methodologies of machine learning is nothing new.  Computers have been able to keep up with the mathematics and now skilled scientists are using these techniques all over industry. 

Yet to me what is interesting in this article is that implies that machine learning sciences is rising from basically nothingness.  As if this is some sort of new fangled technology developed by IBM for a special man vs. machine Jeopardy act.  I guess I'm a little too close to the Operations Research community to know where the roots really lie.  For one I'm happy that decision sciences like machine learning are getting more and more recognition.  On the other hand I'm thinking "Where have you been since World War II?".  I guess I'm a little too cynical lately.

I love the OReilly Radar blog as it seems more and more articles are about the promise of data analytics.  I guess I'm just wishing for a little more investigative reporting.  In fact I think it would benefit INFORMS if they partnered with OReilly Media.  OReilly definitely has a focus on analytics now and INFORMS is prime to provide a lot of great content for discussion.