What’s a good way to analyze data? How do you know if you’re actually looking at data in a way that provides a valid analysis? It’s entirely possible to statistically look at a set of data, run some aggregates, build graphs, and come to a conclusion (or recommendation) that would hurt your business rather than help it.
In academia, many people have their analysis and conclusions reviewed by their peers. Over time, many of the people analyzing data learn from others and start to build skills in how to look at data sets and consider the interpretations that seem to be more valid. Of course plenty of mistakes are still made, but I think the quality of analysis is pretty good overall.
In business we are often working in silos, in semi-secretive ways where our analysis might not be questioned or reviewed. How do we build some skills? One way might be to do what Dev Nambi did, publishing an analysis of college costs and including his thoughts on what the data shows. You could also look at this crime report from Samuel Vanga.
I thought this was a great example of taking a set of data and trying to make sense of it in a variety of ways. While you might have your own thoughts on what conclusions and implications to draw (leave comments about that for Dev on his blog), I think this is an interesting way to approach analysis of a set of data. Many of us could experiment with different visualizations and the analysis of this (or other data), and get comments on our approach.
For example, I find the stacked bar graphs more difficult to understand than a series of line graphs. I also would like a bit more context in what the author sees as an analysis of each graph, but those are my views. Perhaps if I wrote an analysis of some set of data, I’d find others would let me know the ways in which I present my findings are flawed or difficult to understand.
I’d encourage you to practice building analysis, along with other skills you find useful in your job. While most of you can’t use business data on your own blog, perhaps you can find a data set that’s interesting to you and dig in to see what information you can extract and present.