I had a quick look at the [IBM SPSS advertising material](ftp://public.dhe.ibm.com/common/ssi/ecm/en/ytd03023usen/YTD03023USEN.PDF).
It sounds like its part of a general move on the part of IBM/SPSS to get involved with predictive analytics.
Terms like automatic data preparation, boosting, bagging, and automated model selection are popular in data mining and predictive analytics communities.

In that sense you may see similarities with open source tools like [Rattle](http://rattle.togaware.com/) and [Weka](http://www.cs.waikato.ac.nz/ml/weka/).

You might find useful [this article by John Maindonald introducing data mining](http://maths.anu.edu.au/~johnm/dm/dmpaper.html).

In summary, if you have some combination of the following factors, then such tools may interest you:

* interested in building predictive models (as opposed to testing apriori hypotheses)
* you have lots of data
* you want some hand holding on the steps of data analysis