Like Doctor Dolittle's famed pushmi-pullyu, enterprise data projects have a serious agility problem. A recent story comes to mind. I was on a call with prospective customer to request data feeds for an analytics project.  We had performed a successful trial project, the business case was approved by management and everyone was happy. At last, we were ready to go into production. We simply needed data feeds for two well-known, standard tables from a commonly used enterprise system. We'd already worked with an extract and had everything set with the integration and analysis...

Much electronic ink has been spilled on the rise of the data scientist. They've been called sexy. They've been called unicorns. And, we clearly see a direct correlation between this recent adulation and the uptick in searches for "sexy unicorn". (At least, I hope that's the reason). As discussed previously, capturing a unicorn is great if you can find it, but it takes a village to get data stuff done in the enterprise.  Michale Mout once put together a Venn diagram based on the Wikipedia definition of data science: In the response to...