Can you mention a few more?
Not getting all the relevant business constraints. What a way to look bad and lose the trust of your audience. "Oh, sorry, I did not realize that undermines our main client's contract and breaks the law. My Bad".
Not understanding the distribution of the population (i.e. assuming that the sample is from a normal population when it is not) and making inferences based on wrong assumptions.
Data computation and analysis takes a long time to react.
No. 5 applies to any project, of course, not just data analysis. While this mistake may seem like a 'no-brainer', my experience has been that it's common to finish an effort and not know if any real problem has been solved. While everyone will agree it has been, this is more a 'policy of success' than any actual measurable demonstration of it.