Helpful do's and don’ts of data visualization

Data sets are valuable only when people can clearly understand them. Data visualization is one of the best ways to display large amounts of information when done right. It displays data simply as well as intuitively. However, to make sure that visualizations are effective, it is important to avoid a few all-too-common mistakes and follow a few standards.

Data Visualization Do’s

Keep the visualizations simple

Although many people assume that infographics, complex graphs, and charts are very useful visualization tools, the opposite is true. Besides, good visualization can make the main data points easy to understand and simplify messages. Effective and simple visualizations follow these guidelines:

• These visualizations show the full scale of the graph. If necessary, these then zoom to show the data of interest.

• Simple visualizations aim to grab attention by making their point and conveying information in under five seconds.

• They minimize attention-grabbing elements such as colors that are not directly related to the data of interest.

• Use traditional pie charts, bar charts, and line graphs. These are popular and simple for a reason!

• They include titles as well as clear labels to explain important chart elements.

Pay attention to the usage of color

Using color intentionally and effectively will allow you to get your point across. Consider using colors related to the topic being discussed, limiting the number of colors to minimize distraction, and using shades of the same color for comparisons. Be mindful of colors with specific cultural associations or colors that have strong connotations, such as green and red. Such colors can be confusing or misleading for your audience.

Know your point

You can make sure that the visualizations you choose will be relevant by knowing your point before you do the work. Knowing your concluding point before starting to spend any time creating infographics, graphs, or charts is one of the easiest ways to approach data visualization. By knowing the exact point you are trying to convey your audience, you can make sure that the data visualizations you select will support your conclusions.

Tell a data story

One of the most prevalent misconceptions regarding data visualization is that it conveys the audience what they need without much additional context. Not focusing solely on the visualization and assisting the audience to build the picture through a story can make the data visualizations stronger. Apart from that, this will help your audience to remember the information for a longer period and make data more accessible to your audience.

Learning the effective development of data stories can be one of the strongest data visualization skills. We can achieve these visualization skills with some thoughtful planning. A story allows your audience or viewers to organize the points you are presenting in a more consumable as well as logical manner. Besides, it keeps them engaged in your presentation.

Seek feedback and help.

When you create data visualizations, having someone else review these visualizations to provide constructive feedback is one of the best things you can do. By making sure that the visualization is understandable, you are providing a fresh perspective to the audience.

Data Visualization Don’ts

You must avoid visualization don’ts. A sloppy and bad visualization can inadvertently result in misrepresented data. Such data can be dishonest at worst and discrediting at best. However, some tips can keep your visualizations honest as well as effective.

Don’t misrepresent data intentionally

Although this seems like a no-brainer, it is very important to mention. Misrepresented data has consequences regardless of whether it is done intentionally or unintentionally. For instance, several errors can undermine your reputation and the validity of the data set:

• Using inappropriate colors for the described data set

• Usage of uneven intervals between the numbers

• An axis that starts at a particular place that exaggerates differences within the data

• Using inconsistent or inaccurate scales on size comparisons

• Thinking about how the visualization could be misrepresentative or misleading is the responsibility of the data experts who put together a visualization.

• Don’t try to present too much information

It can be confusing and just plain ugly to squish too much information into your visualization. Here are a couple of tips to make your visualization informative. If the chart is crowded, would be difficult to effectively differentiate between different data points within the first couple of seconds. Usage of are more than six colors in your vision is not recommended. Sometimes you might need multiple text boxes to explain different data points.

Using bad data

Data visualizations are largely affected by the data behind them. Data visualizations will have inherent logical flaws if you start with faulty data. This would even affect creative data visualizations that are matched with a well-crafted story.

High data quality is especially important to create data visualizations and a necessary foundation for all data systems. Data quality should always be a priority. Think quality over quantity and do not try to use all your data. Data visualizations try to distill the required data points to the most memorable, relevant, as well as interesting. Make comprehension your priority. A well-crafted infographic will be useless if the reader cannot easily comprehend or quickly understand the key points. A graphic has to be attractive as well as informative. Try not to include unnecessary visual elements. Remove anything that is not contributing to the broad data story. Try to review the layout of data visualization with a careful eye. You should utilize a hierarchy in visuals. Make sure the data is intuitive as well as organized. Try to order all data by value, sequence, or alphabetically. These techniques and tips will make your visualization interesting and intuitive when you are ready to dive in or create. By using specific and helpful visualization, the users can digest it quicker and easier.

It would be good to research what format will work the best for your audience and your business before jumping into the design. Studies suggest that the human brain prefers to look at bar charts instead of pie charts. Besides, scatter plots can be more easily processed compared to line charts. Engaging content is more powerful as it grabs the attention of the consumers, unlike static content. Following some simple tricks and tips can add interactivity and be a game-changer. You can allow your users to customize the graphic by zooming in or out. Clickable controls are some of the primary practices to be followed. Try not to go overboard with the vibrant colors. Do not obscure the data or forget about the users with color vision deficiencies. If you want to show individual components accurately, use a stacked area chart. Do not use a chart when a sentence will do. Design for comprehension and always choose an efficient visualization. Keep graph and chart headers simple and to the point. Watch out for negative and positive numbers. Include a zero baseline if possible and do not use numerous colors in a single layout. Choose the chart that tells a story.

Try to use colors the right way. Your data visualization stands out with the usage of the right colors that are attractive to the eyes. Wrong colors can Divert the audience’s attention by making your data visualization confusing. Apart wrong colors can drive them away from your message. Avoid using bad data that is out of date and inaccurate. It could come from an untrustworthy source. Bad data doesn’t make sense to your audience. When working with charts precisely define your message to your audience. Remove items that do not serve this message and add data that illustrates or conveys your message.

Conclusion

Data visualization has several key business benefits. Nowadays the data visualization experts in the market utilize a variety of tools to make sure that your business data is represented in a consistent, clear, as well as concise manner. This allows companies to leverage the information in a way that is beneficial to them. Apart from that, this will allow businesses to gain an edge over their competitors. Your visualization has to be pretty as well as informative. Businesses should make comprehension their priority. Create a beautiful infographic that the reader can quickly and easily comprehend. You should have a specific message you want to communicate before you create data visualization.

You will be more likely to accomplish your target if you understand what information you want to get across. As too many colors can over-complicate your visuals keep your colors to a minimum. Do not overwhelm your reader by making data comparisons difficult. A consistent color representation is essential for data visualization. If the data is appearing in multiple charts, use the same color to represent a specific piece of data. This will allow your reader to see trends and scan the overall visual better. Make sure that your data is intuitive and organized by utilizing a hierarchy for all your charts. Try to order your data alphabetically or by sequence.