"I've said it before, but if digging into data is your idea of fun, there's a whole mess of excitement and adventure headed your way. There are lots of opportunities already out there in marketing, journalism, tech, the Web, government, and pretty much everywhere you look. And more importantly, there are lots of opportunities that you can make for yourself. This is a great time for data heads."

This was the first annual Data Scientist Summit, and I will no doubt be back. With that said, discussion of technical topics had a bit of an introductory flavor to them, which made the discussion of the technology seem dated. For example, “Vanilla” Hadoop was introduced as a tool for processing vast amounts of data. I would expect that most Data Scientists have worked with Hadoop, or at least know what it is. Hadoop is somewhat old news in terms of “cutting-edge technology.” Tools like Pig, Cascalog, HBase, Hive, Cascading, etc. would have been a better discussion topic. I was also disappointed with how little coverage of tools (except for Hadoop, NoSQL, and enterpise databases) there was. It seemed as if R had gone M.I.A. and I was surprised that there was such little discussion of visualization tools like Tableau, Processing, Gephi, D3, Polymaps, etc.