Distribution charts are underestimated by Data Analysts.
I see very few of them in production on a daily basis.
And yet, these kinds of charts have incredible analytical potential.
The drawback is obviously the number of brands displayed, which can be a source of frustration for users.
There are several reasons for this:
- Too many marks slow down dashboard performance (usually).
- High cognitive load disengages users.
- Less is better, always.
Ask yourself the question regularly :
“Do I really need to display a scatter plot with 45,000 marks to help my user make a decision?“
98% of the time, the answer is “No“.
-----
PS1 : Support my work by tagging someone who's developing a dashboard and may need this resource.
PS2 : Follow me for a new illustration each week.
#businessintelligence
#datavisualization
#dataanalytics
I see very few of them in production on a daily basis.
And yet, these kinds of charts have incredible analytical potential.
The drawback is obviously the number of brands displayed, which can be a source of frustration for users.
There are several reasons for this:
- Too many marks slow down dashboard performance (usually).
- High cognitive load disengages users.
- Less is better, always.
Ask yourself the question regularly :
“Do I really need to display a scatter plot with 45,000 marks to help my user make a decision?“
98% of the time, the answer is “No“.
-----
PS1 : Support my work by tagging someone who's developing a dashboard and may need this resource.
PS2 : Follow me for a new illustration each week.
#businessintelligence
#datavisualization
#dataanalytics
