The "Training Students to Extract Value from Big Data" workshop just ended, and I have to admit to being quite steamed at the attitudes expressed. This workshop was funded by the NSF Big-Data initiative, but the money was given to the National Research Council's Statistics branch, not to the branch that handles CS. As a result, although there were a few computer scientists there, the majority of attendees and speakers were statisticians. Two of the speakers showed in their slides the same offensive Venn diagram, whose three components were Math/Stat, Domain Science, and "Hacking." Machine learning was defined as the intersection between Math/Stat and "Hacking." And the intersection between "Hacking" and Domain Science was labeled "danger area," as if a computer scientist should not attempt to interact with an application area without the wise guidance of a Statistician. Another participant expressed the position that, granted Locality-Sensitive Hashing was an intellectually interesting and useful idea, it must therefore be a branch of machine learning. Yet another Statistician mentioned that he chairs a committee of the American Statistical Association to define a curriculum in "Data Science," and he saw no reason why SQL should be a part of this program. I could go on, but I think I just calmed down a little. Thanks for reading this.