If you are frequently working with data, using charts to make it visual it is obviously an absolute necessity. You can spend weeks gathering and analyzing tons of data, if you are not able to communicate it effectively to your audience, this is just a waste of time.
Unless they are able to read in the Matrix, nobody will understand or remember more than a couple figures of quantitative data on a presentation.
So you better make sure you make it visual! And for this you should use charts that will present your data in a much more legible way.
Using the right type of chart will help you in many ways:
Charts make your data easy to understand
Charts help people quickly see the key trends and the orders of magnitude
Charts are easier to remember than large list of numbers
Charts allow you to highlight the key insights your audience should focus on to extract actionable information
Table Vs chart: which is easier to understand?
What does a good chart looks like? Well a good chart should be 2 things:
Insightful: wether it shows a trend, a comparison, or an order of magnitude, a chart should detinitely carry a message. If you can't say anything interesting when looking at your chart then it's probably better to just delete it: it means that there is nothing interesting to say about your data.
Visual: the design here is obviously important. The better your chart look, the higher the impact will be.
This is where choosing the appropriate chart type is strategic, because it will allow to make your data both insightful and visual.
What chart should you use?
To know which chart you should use when, we have created this infographics that you can use as a toolkit every time you need to display your data on a chart.
Before you rush in creating a graph, ask yourself this: what do you want to do?
Do you want to make a comparison?
If so, you should consider one of these graph types:
A map if you are comparing geographical data
A radar if you want to compare different qualitative features
A bar chart of column chart for other types of comparison. Prefer column charts if you have only a few series. But if you have many series, a bar chart will keep the names written horizontally and will be easier to read.
Do you want to show how a value evolves over time?
If so, you will probably be happy with one of these charts:
A column if you have a few non-cumulative values
A stacked column if you have a few cumulative values
A line chart if you have many non-cumulative values
A surface chart if you have many cumulative values
Do you want to show the composition of something?
Yes? Then you will opt for one of these graphs that break down data series into cumulative components:
A pie chart or doughnut if you have 1 series
A stacked 100% column chart if you have a few series
A Mekko (or Marimekko) graph if you have a few series with a sub-composition
A Treemap if you have many series
A Waterfall chart (or Bridge chart) if there are both positive and negative values that are cumulated to make the total
Do you want to show how something is distributed?
Then go for one of these:
A bar chart if you have 1 dimension and a few data points
A line chart if you have 1 dimension and many data points
A scattered plot chart if you have 2 quantitative dimensions
A bubble chart if you have 3 quantitative dimensions
Hopefully this guide will help you present your data in a visual, relevant and appealing way that will help you engage your audience. Feel free to comment if you have any suggestion to improve this!