If you were to list the top half dozen overhyped, buzzy topics in IT these days, I'm sure Hadoop would make the list. Hadoop is an open source framework for analyzing large data sets across horizontally scalable clusters of computers. And while Hadoop doesn't require the Cloud, it's obviously a good fit.
Hadoop may still be mostly hype, but if you're looking for a new skill to pad your resume, Hadoop is a great choice. After all, Big Data are all the rage, and the fact that Hadoop can bring the whole Big Data and Cloud hypefests together into one big party translates into a huge cha-ching for anyone who can actually get the stuff to work.
Of course, if Hadoop were easy, then everybody would be doing it. But it's not. As they say in Boston, it's wicked hard. But you're a tech guru, right? You live and breathe Java. How hard can it be?
True, Hadoop is a Java framework, so you Java gods out there, take note. But remember, the point to Hadoop is to build complex analytics algorithms across large data sets. How often have you done that with Java?
Ah, there's the rub. If you're a data analytics geek, you know all about complex data queries and analytics algorithms. But you're probably not a Java jock. But if Java floats your boat, then the world of the data geek is probably mostly alien to you. And you won't be able to fake it by knowing a bit of SQL.
So now you know why there's so much cha-ching in being a Hadoop expert. You need strong Java skills as well as strong quant skills. And people with both are very hard to find.