In general, most data scientists don't need to see the entirety of a data set to get an idea. A lot of the initial data exploration is about separating signal

In general, most data scientists don't need to see the entirety of a data set to get an idea. A lot of the initial data exploration is about separating signal from noise...what of the data is important. After that (similar to your examples), it completely depends on what you're trying to see. Am i looking at per capita data? Then chances are simply toss it at a choropleth. Time series tends to work pretty well in a simple linear graph type structure (as one will often overlay), etc.