I couldn't agree more with your statement, good sir. Data is beautiful, but also frightening if the right parameters, sample, population, calculations etc are not selected appropriately for the question you ask about the data. When these categories are not chosen correctly for your data calculations, then you can misrepresent any point very easily. So much as removing a potential outlier can have significant impacts on the final representation of said data.

So many comments mentioned how this set of data was unfair because it did not include smaller corporations with CEO's, or didn't account for the type of pay they were receiving in comparison to company employees. Those sorts of questions would require additional data and calculations, and could also water down results and muddle the point the graphic/author wanted to make.

On the other side of things: I agree that there is a sample bias here over all, but the intent was to see a glimpse of merely the top 350 company CEO's income disparity over a long term period. Further investigations into the data could be done to see if the initial graphic is still significant or not.

This is just my two cents from being a student in stats. Take it, leave it, burn it, hate it, be my guest. =P