At my work, I have the pleasure of being involved in a big data project that uses Hadoop as the primary platform for several services. As an architect, I try to get to know the platform's capabilities, its potential use cases, its surrounding ecosystem, etc. And although the implementation at work is not in its final form (yay agile infrastructure releases) I do start to get a grasp of where we might be going.
For many analysts and architects, this Hadoop platform is a new kid on the block so I have some work explaining what it is and what it is capable of. Not for the fun of it, but to help the company make the right decisions, to support management and operations, to lift the fear of new environments. One thing I've once said is that "Hadoop is the poor man's mainframe", because I notice some high-level similarities between the two.
Since 2010, I was at work responsible for the infrastructure architecture of a couple of technological domains, namely databases and scheduling/workload automation. It brought me in contact with many vendors, many technologies and most importantly, many teams within the organization. The focus domain was challenging, as I had to deal with the strategy on how the organization, which is a financial institution, will deal with databases and scheduling in the long term.