Data visualization mistakes to avoid

Posted on Tuesday July 21, 2015

Data visualizations are common in business presentations today. They can provide us an overview of information and results in a simple and easily digestible way. Good data visualization helps users to understand data in order to make informed decisions based on the findings. Bad data visualization, on the other hand, will provide little to no value for readers and make complex data even more difficult to comprehend. With that said, you can present data in a better way by avoiding these common mistakes.

Inconsistent visualizations

It's important to be consistent when presenting your data, otherwise users will have to stop and figure out how to read each new picture before they can comprehend what it says, wasting time and defeating the purpose of data visualization. Luckily, there are some best practices you can follow. For instance, try choosing colors that go well together. Use only 2-3 colors at most throughout your visualization - any more and you'll find that your pictures might be hard to read. Also, use the same iconography and typography in each picture so your audience can quickly understand the information.

Displaying too much data

Overly complicated data visualizations are sure to turn off most audiences because they can't figure out where and what to focus on. Your customers, colleagues, and employers want specific, relevant answers. The quicker you can deliver those answers, the better. Irrelevant data gives your presentation a cluttered look, making finding relevant information more difficult for readers. The solution? Find a compromise between showing too much data and not showing enough overall. Use good judgement.

Oversimplifying data

The purpose of data visualization is to present data in a way that's easy to understand. While it's all too easy to simplify data, if you go too far and leave out crucial parts, your audiences won't be able to see or grasp the main point of the presentation. Instead of trying to oversimplify data, it's better to include all important criteria and organize them into a structure so audiences can easily understand what's being presented to them.

Choosing the wrong visualization

This is one of the most common mistakes made in data visualization. There are many different types of data out there, and each of those types require different analytics and tools to use. For example, if you want to present a sales growth comparison in the last 5 years, it's better to use bar charts that can clearly show the difference at a glance. If you want to show a relationship between two metrics, on the other hand, you should use a scatter chart to show results.

The best way to avoid all these errors is to focus on your goals first. It's likely that you'll have to make changes along the way, which is actually a good thing, because it will make your presentation more accurate and effective.

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