Follow 10 rules to create clear, impactful charts and diagrams that simplify complex data, tell a story, and support better business decisions.
Charts and graphs have become a staple in many areas of our day-to-day activity. From business reports to television to sports and games, they serve to present often complex data in an easily digestible form. The way you create these graphic representations of information will be affected by their exact purpose and the medium they'll appear on. You'll have to account for various factors in order to develop a useful chart. Stay with me to learn how to make a good graph that actually makes an impact.
A badly designed chart can not only be an eyesore, but also lead to imprecise or incorrect conclusions.
Regardless of what exactly you're aiming for with your visual data representation, there are several fundamental rules you should observe in order to make the most of it. Before I move on to discussing them, let's make sure we understand.
The problem with data analysis is that it can quickly get too complicated for humans. Thus, it's crucial that the numbers we're trying to process are served in a form better adjusted to our perceptive systems.
Vision is perhaps the most well-suited sense for the purpose of information processing so encoding intricate data points visually is a good strategy for anyone looking to obtain quality insights.
Now that we've established why data visualization is important and useful, it's time to lay a framework for effective graph design that will prove to be a difference-maker in terms of reaching the audience with your message. Take a look at the following tips and try to apply at least some of them the next time you're working on a visual representation of data.
1. Ask yourself a question
You're going to have a tough time creating an effective graphic representation of data, not having a set goal in mind. Start off by determining what it is that you're looking for. What answer should the chart provide, and start building around that.
2. Know your audience
Consider who's going to view your graph and what they'll be trying to get out of it. In what context or medium will they come in contact with the chart? How are they going to interact with it?
3. Make sure your data is on point
The set of information you're dealing with constitutes the basis for all the charts and graphs you design. Quality data will make for quality diagrams. Working with particularly extensive databases, it may be wise to do some data cleaning first.
4. Choose the most suitable representation for the data
When trying to decide which chart type to use, think in terms of what the audience needs to learn from it. This ties back to the first rule about the purpose that the graph is supposed to serve. So again, what type of diagram will help people see relationships, parts of the whole, distribution, compare data points?
To choose the most suitable visual format for your data, consider these additional questions:
5. Color scheme
Even though it may seem like a negligible part of the process at first, choosing colors that go well together is no small matter. In general, less is more so try to keep them to a minimum and matching. On a related note, a good rule of thumb is to have a white background, as it keeps the focus on what the data is saying.
6. Explain encodings
Whether you're using a color scale for magnitude, the size of a square to show particular values, or maybe a combination of other styles, you want to explain to your audience what your encoding is supposed to mean. A regular legend labeling shapes and other elements or a short descriptive paragraph will work fine.
Note: A legend isn't an absolute must with each and every chart. Visuals may be self-explanatory enough, especially with the help of concise accompanying labels.
7. Emphasize the important part
The graph you're working on should have a clear focus. The goal is usually to make and emphasize a particular point. A good graph will do this visually and immediately inform the viewer what the main takeaway is.
The focus can be achieved in a variety of ways including the color, size, or weight of the elements/indicators, as well as bolding or circling some of the information pieces.
8. Consider the UX aspects
What makes a good graph is its focus on the user. Some things to take into account to ensure great UX include:
9. Include sourcing
When creating your graph, don't get too caught up in all the arrows, columns, and other objects. Remember to always finish off your design with sources for the presented information. This adds legitimacy to your work and allows the audience to fact-check and dig deeper if they decide to do so.
10. Make your chart design stand out
Diagram creation isn't just about presenting cold hard facts in the most minimalistic, to-the-point way possible. It's also somewhat of an artistic endeavor.
There are many ways to make your data visualization emphasize the point and be remembered. Creativity is boundless and in this context goes beyond the stiff frames of particular chart types. Don't force it or try to apply this rule each and every time but if an interesting idea springs to mind, don't hesitate to enhance your graph with it and create that extra flair.
Creating memorable data visualizations can be a challenging task. Not only do you have to process and analyze the data but also turn it into a beautiful design. This requires different skillsets and software to achieve.
With the tools available in the market, you are capable of making this happen on your own, however, if by any chance you don't feel like venturing into this avenue, Synergy Codes is here to assist you.
Feel free to contact us anytime in case you'd like to commission your graph design work to a team of professionals experienced in the matter.
All in all, data viz isn't only about aesthetics, it has a specific function to perform. The goal is to make the presented information easy to understand and so drive faster and more efficient business decisions,
In order to create a good graph that really makes an impact, it's important to know and follow a set of rules discussed here providing a framework for efficient data visualization. These guidelines aren't set in stone and may be bent in specific cases.
Still, it's good to keep at least some rules for graphing when trying to communicate complex datasets.
At the end of the day, above all other chart rules covered, you should aim for clear storytelling and precise communication of data. As long as you check these boxes, you'll be able to produce bar graphs and flowcharts that reach their audience and create a positive impact.