5 Data Visualization Best Practices

Data visualization is an essential part of any STEM, history, marketing, and finance industries to efficiently present their data. The reason is that plain numerical data isn’t the most effective way to analyze, especially when it comes to learning a trend. Data visualization can help people understand better by providing a useful chart or graph.

In marketing, for example, data visualization is very much needed to analyze a campaign. It helps marketers to examine the metrics in an easier way, mainly in regards to analyzing big projects like an explainer video. This campaign is used to create awareness and generate conversion rates through its call-to-action.

In other words, tracking and analyzing the conversion data can be challenging when visualization is neglected. Marketers will find it hard to plan the next campaign without a simple data visualization.

The same analogy goes to the other industries where data presentation is a part of their businesses’ activity.

The Importance of Data Visualization

Data visualization is essential in the first place because most people are visual learners — they are most likely drawn to color and pattern. They can identify a data difference faster than a straight numerical presentation. Therefore, by visualizing data, you can make the information clearer for the audience.

Data visualization is a complete curation of larger data in the form of graphs, maps, or charts. That’s because people don’t need to understand extensive information in a raw form. Crafting data visualization from a rough report can be hard if you don’t understand the guidance to create.

So, here are the five best data visualization practices to follow:

1. Know Your Audience

You should know and understand who your audience is so that you can address their needs. Understanding your market segmentation makes it easier for you to create an understandable data visualization. This, in turn, will help you to make a helpful presentation that brings a solution to your audience’s problem.

Therefore, you need to develop a viewer’s persona that best represents the target market. From this point on, you’ll understand what they need and how you can benefit from this by bringing insightful data. You can also craft a delightful material that urges people to take action immediately if you need it.

2. Select The Right Visual

There are many types of data visualization in the form of graphs or charts. However, every visual has distinct features in bringing the information effectively. For instance, you can’t implement a random map for the audience who might not understand how to read it.

Here are some of the standard charts used in data visualization:


A table has its benefit to present a lot of information in a single go. This structural visual can have multiple rows and columns that showcase the actual data ultimately. However, most people can get overwhelmed if presented with far-reaching table data.

Line Graph

A line graph measures changes or trends over time and shows the relationship between two or more variables. This type is apt for those who are seeking a trend from a different variable.

Bar Charts

Bar charts are better used when comparing the various amounts of a different group.


Heatmaps can display data graphically where the individual values are presented in a different color matrix.

3. Emphasize Important Points

Data visualization allows you to highlight important information that you want the audience to know. Using a specific color, different font, or making extra information will let the audience identify the crucial information better.

To emphasize your points, you should be able to guide your audience to follow the storyline of your graph. One of the examples is to create information orderly. If your chart is read from left to right, you need to ensure that your highlight points follow the same order. This way, you can guide the readers to understand what your image conveys completely.

4. Keep It Simple

More often than not, a lot of information makes it difficult to develop your data charts. Most people probably think that every piece of information is important to be delivered to the public when it’s not. Your targeted audience can get overwhelmed with too much data.

A simple graph doesn’t necessarily mean uninformative or lack of research. On the contrary, the simpler your data visualization is, the higher chance of readers understanding what message you try to deliver.

5. Provide an Effective Label

This part is one of the essential practices that people often overlooked. Data labels let the readers know which variables are there and how they interact in a specific manner, especially when you have a new variable that needs to be told.

By labeling your graph effectively, you won’t let the audience guess which information is being conveyed. In short, your data visualization must be readable for your readers (whether they’re a noob or a pro) without providing extensive back-up data.


Data visualization is vital for many sectors of industries to present the information effectively. With visualization, you let the audience identify the data faster as the human being tends to find patterns in the first place. However, without a clear understanding of making data visualization, your whole information can be a mess. Therefore, it’s essential to find out which visual is apt for a different audience.

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