What are they?
Pre-attentive attributes are what we as data analysts must use to help tell the stories that we want to tell. They are information that we already have stored in our brain.
If we take length for example, we immediately understand what it means if one bar where to be longer than the others. All the attributes shown above are different ways of highlighting a point and drawing attention to it. The reason these attributes are so important for a data analyst is because often we are trying to convince the audience of something with our visualizations. Making the most of pre-attentive attributes ensures that we are lowering the "barrier of entry" for the user. Users feel familiarity with the charts and know exactly where to look and immediately start to understand the visualization despite seeing it for the first time.
If attributes are over used or too many are used at once, then it can get boring or go to far and create a lot of noise. The user will have no idea where to look or wont be interested anymore.