Choose the right data visualization toolĭata visualization should be done precisely but not in a time-consuming way. While you’re already familiar with your data, show the design to a friend or colleague – can they get the whole picture in less than 30 seconds? If so, you did a great job!ĥ. This will help your charts and graphs look more professional. If presenting data on behalf of the organization, always try to use the company’s branding: colors, fonts, and styling.Use them only if they actually facilitate the readability of the graph. Add data labels directly to the lines or bars, especially if it makes the chart easier to read at a glance.Bright colors attract eyes more quickly, so use them to attract attention to a specific part of the graph. Instead, choose one tone for the chart or add another if there’s a need to highlight data. Try to avoid mixed or rainbow color palettes – they tend to be ineffective.This is important to make sure the viewers get the message clearly. Choose a font for the title, axis labels, and legend that is easy to read.Learn these crucial data visualization tips: While the content should be visually appealing, you should avoid having too many colors, fonts, layouts, and accents. There’s a thin line between good visualization and not-so-good. Add the source of data to build credibility and trust, and to provide an opportunity to learn more.Tell the whole story instead of only showing the most impressive numbers.Organize the data logically to ensure they’re easy to compare at a glance.Make sure the labels and legend are easy to read and understand.Scale the chart appropriately with equal intervals on each axis. Create a strong title that builds up the message you’ve set in the first step.Include only necessary data – if it doesn’t support the story, leave it out.To provide full context of the displayed data, follow these tips: Dataviz is not about numbers that are put into colorful bar charts – it’s a set of visually displayed information that should be comprehensive yet easy to understand. Keep in mind that every data visualization project should provide value for the audience. To better understand each chart type in detail, watch our video about how to choose the right chart for your data. To show how items are distributed over time and to identify the trends, distribution charts are very useful. For example, to show the relationship between fertility rate and life expectancy in different nations, the best fit would be one of the following:Ĭomposition charts express the structure of a total and change over time (e.g., distribution of your monthly expenses). To reveal the connection or correlation between two and more variables, the relationship chart is the perfect match. They are also used to measure items and highlight trends over time, such as the average temperature in Tokyo for the past 3 years. There are 4 main types of charts, based on what you’d like to express.Ĭomparison charts are the right choice if you want to compare variables from one or many categories (e.g., sales by department). Once you’ve set the goal of your dataviz project, it’s time to put the numbers into a graph to emphasize the message. One size does not fit all, and that’s true for data as well. Choose the right chart type for your data visualization Setting the goal and choosing the target audience are important elements for a good data visualization, not just because you’ll have a clear vision of the outcome, but also because you can choose the correct chart for your data. It should be easy to process data and understand the message as quickly as possible.įor example, the depth and approach to how an organization’s management communicates the data for stakeholders or employees will be much different than educators explaining concepts for students or marketers building awareness on social media. Choose your target audience to create charts that are compatible with their knowledge and expectations. When you’ve clarified the main message, it’s time to identify for whom it’s addressed. Whether it’s a performance overview, behavior analysis, process efficiency review, or a call to action, the message of your story must be clear. Set a goal and clear messageĭata visualization plays a vital part in communication, so you have to set an achievable goal and a clear message. In this article you’ll learn 5 best practices on how to create impactful data visualizations. On the other hand, publishing bad charts and graphs can lead to detrimental results. If done right, data visualization can become an important asset to reach goals and engage audiences for businesses, educators, marketers, sales and project teams, and everyone else who works with loads of data. That is why the credibility, visibility, and comprehension of the information are so important.
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