Data Visualization Tips for Enhanced User Experience
Did you know that 90% of the information transmitted to the brain is visual?
Did you know that the human brain can process an image in just 13 milliseconds?
Did you also know that high quality infographics are 30x more likely to be read than plain text?
The truth of the matter is that Data Visualization is the smoothest way to share information. The tips below will assist you in building a better Data Visualization for your readers.
Goal and Audience
Before selecting any one of the types of data visualization, you need to focus on the goal and the internal/external audience your data serves. Your data research and data presentation must be guided by this principle. When choosing multiple data sets to research, having a crystal-clear purpose can help you to know where to start. You must take into account: i) What information is the target audience looking for? ii) What are the questions that can be answered through the planned visualization? iii) How to compare different data categories iv) How will the final data visualization appear to the readers? v) What will be the last touches to add
Selecting a Suitable Format
Different data visualization formats can be used for the representation of facts and figures. There is no one best data visualization format. When comparing categories within a single metric, bar charts are helpful. They are a convenient option when you have data that can be divided into several groups. Bullet charts compare metrics to illustrate progress toward a goal. The line graph joins multiple different data points to create a continuous progression. As a result, it's simple to see how one value changes in relation to another. Maps can be considered to indicate geographical locations or to help in geographical research. A pie chart is a circular statistical visual that is divided into parts to show numerical proportion.
Take Advantage of Shapes and Designs to Incorporate Contextual Clues
Instead of sitting and interpreting complex data, context allows us to decipher it at first glance. Shapes and designs can tell an intriguing story. For example, the shapes of animals and color shades can represent the species that are in abundance and endangered in a particular region of the country. Creating a bar chart or pie chart for such a representation can be confusing to the readers.
Add Colors for Visual Aid
While using data visualization tools, colors can be used to draw the attention of the readers. They can convey crucial information and even highlight outliers or oddities. While adding colors to the Data Visualization is a great step, you must do away with it if it fails to add meaning or improve the intended interpretation of the data. Individuals can only differentiate between 5 to 8 colors at a time. You can apply different colors for showing Quantitative Data for suggesting an order. For instance, a temperature of 45°C can be shown in ‘red’ but 15°C can be indicated in ‘orange’.
Layouts Should Follow Predictable Patterns
We are wired to look for patterns, and if the patterns are random or don't make sense, it's tough to decipher what the Data Visualization is trying to say. Make sure the sequence or the pattern in which you show data makes sense to viewers, whether it's quantitative, alphabetical, or sequential. Capitalize on human impulses. For instance, if you're using numerous graphs, make sure they are in the same sequence and that the links between the data are obvious. You don't want your viewers to be lost when they navigate from one point to the next.