Which Chart Should I Use and When? A Guide to Dashboard Charts Pt 2

With the advanced offerings of many BI solutions nowadays, you are often met with more types of chart than you know what to do with. But, remember, they are there for a reason : each one is useful in its own way. The trick is just knowing which one to use, and when. Hopefully this article will give you a better understanding of some of the more common charts you might be using. To the casual user it may appear that different charts can simply be used interchangeably, and this is often the case, but not always the best solution. Experts have come up with guiding principles that can be applied to achieve maximum data visualization effectiveness. This also comes at a time when viewing data on mobile devices is becoming more and more popular, and this should be taken into account too.

This post follows on from Which Chart Should I Use and When? A Guide to Dashboard Charts Pt 1.

To recap, we already covered:

  • Bar charts (and column charts)
  • Line charts
  • Point/Bubble charts
  • Pie charts
  • Sparklines
  • Bullet charts
  • Guages

What else is out there? Special purpose charts.

  • Radar charts
  • Maps
  • Treemaps

Radar charts are optimal for displaying cyclical data with three or more quantitative variables represented on axes starting from the same point. They are often used for the control of quality improvement, or to chart sports players' strengths and weaknesses. Each data point has a vertical axis, which measures its distance from the central point. Goals and thresholds can be put on top to provide context to the data. Radar charts should be used when you want to see visible concentrations of strengths and weaknesses, as well as overall performance.


Maps are probably one of the best ways to display geographic information. They can be enhanced with labels and color and size encoding, to display multiple quantitative metrics.


A tree map is a visualization of hierarchical structures using nested rectangles. It is very effective in showing attributes using size and color coding. When the color and size dimensions are correlated in some way with the tree structure, one can often easily see patterns that would be difficult to spot in other ways. A second advantage of treemaps is that, by construction, they make efficient use of space. As a result, they can legibly display thousands of items on the screen simultaneously.



A problem you may come across in your dashboard once you have chosen all your charts carefully is that of data update. When you update data, this could skew your results considerably, and render some of your visualizations less effective. Unfortunately there is not much that dashboard designers can do about this, it is just a matter of you as the creator to test the extremes of your data set, if possible, and choose your visualizations with the results in mind.

Of course Bime incorporates all the types of chart I have discussed above, plus more. So next time you use Bime to analyze your data, I hope you are able to make the best visualization choices and use Bime to its full potential!

Don't forget to check out our charts in the showcase section.