Apologies for the delayed response - my use of google groups is a bit unpredictable... The point of that blog post was to argue that Scala could and should be a good choice for data analysis. I don't think I was arguing that it already is. Breeze is very good and getting better, despite the sketchy documentation, and that provides a lot of the things that are most difficult to implement. As mentioned above, I think the main thing holding us back is a good data frame implementation that the community settles on. There has been discussion on the Breeze github about developing a new Breeze data frame - that is one possibility. Given a data frame, adding some "statsmodels"-like functionality would be relatively straightforward. A good viz library would also be useful, though again, that shouldn't be fantastically difficult to develop. There is a lot of good Scala ML stuff in Spark mllib, but that isn't possible to use from a regular Scala project, which is rather frustrating... I must admit that for routine data analysis I still mainly use R, but for algorithm development and for "big data" I'm still using Scala and still happy with that choice.