Pick a question. Now that I had a rough idea for what I wanted to visualize, I really needed to focus on what I would be doing. The best way to do that is to chose the exact title you want to give your visualization.
Oftentimes, you might be tempted to start with an answer in the form of a hypothesis or preconception. The results will get might be valid but radically different.
As for the technologies used for data crunching, it’s Pig on Hadoop over a Cassandra cluster:
In my case, we have a Cassandra cluster with information on more than 350 million photos shared on Facebook. I’ve been running Pig analytics jobs regularly to get a view of what we have in there. […] In this case I already had some Pig scripts asking similar questions, so I was able to adapt one of those. The biggest surprise was when I ran into issues with some of the joins. The hard part was running the Hadoop job to gather the raw data from our Cassandra cluster, and that worked. I was able to output smaller files containing the gathered data, and then run a local Pig job to do the joins I needed.
Original title and link: Lessons in Data Visualization: How to create a visualization ( ©myNoSQL)