Free DMTA Tools
One of my favorite free tools dealing with visualization is Treemap
If you were to put together a data portal to constantly evaluate the trends of data in the agency this would be the type of thing that gives a nice overall snapshot of the data and the direction it is going. It also serves as a nice starting point for performing a specific analysis on a set of data. Here is a great example of what Treemaps can do.
The one thing to know about this example is they have taken the free concept and initial source code of Treemap and extended it beyond it's capability to be specifically geared to financial analysis. They charge a license fee if you want to use their extended version.
Traditional statistical/analytic techniques are provided for free by the R project. The R project is modeled after the S project and contains most of the same functionality. R can perform linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and present the results graphically.
The next few free tools are as much source code APIs as they are tools. They are powerful but difficult to use tools that require text and data mining theory to effectively use.
The first tool is Kea. It performs text key phrase extraction. Think of it as a way to figure out key concepts in unstructured text.
The next tool is Weka. Weka is by far the best free (open sourced) software package I have scene for data mining. It contains the majority of methods of data mining discussed in the workshop (data pre-processing, classification, regression, clustering, association rules, and visualization).
Here is an interesting article about an example of someone using Weka and Kea to mine, organize and analyze an internet mailing list's archives.
**Note its been translated from German so the wording is a bit off.
The first chapter of their results is available on line.
One more worth mentioning in the Free Tool Category is JFreeChart - free java class library for graphing
As you can see not all DMTA has to be expensive.
Comments
R is cool.
Posted by: J$ | March 22, 2005 12:20 PM