Data Visualisation - Why Simplicity is Key

Data visualisation is a powerful tool which allows you to organize data in a way that's both compelling and easy to understand. Creating a good data visualisation is not an easy task - one of the best practices of good data visualisation is simplicity! 

data visualisation

Data visualisation is a powerful tool for communicating all kinds of insights. More and more data visualisation platforms are becoming available, making it relatively easy for anyone on the internet to share data in this way.

Introduction: Objectives of Good Data Visualisation 

Creating a good data visualisation takes a lot of thought and effort around not just what to include but what to leave out as well. Simplicity is key and among the best practices for success. After all, data visualisation should be easy to interpret and communicate. Data visualisation should not deceive its audience—a common unintended pitfall. Instead, data visualisation should empower its audience and address their needs. One of the best practices for good data visualisation is simplicity. We’ll explore why it is so essential here

Pitfalls of Over-visualisation

Anyone tasked with creating a data visualisation understands how enormous a task it can be to condense a lot of data into a simple chart or dashboard. It’s a necessary process, however, because there are real pitfalls of over-visualisation that can impact the overall effectiveness and values.

Including too many design elements and stuffing too much information into one visual happen too often. These often go hand-in-hand with bad design and charts that are hard to understand. When any of these occur, you are at a real risk of sending mixed messages and coming up with a presentation that doesn’t meet its objectives or communicate effectively with your intended audience.

You can find an example of over-visualisation in the map below. Too much information crammed into the visualization make the it difficult to understand.

 

data visualisation complexSource: Hubspot 

Over-visualisation often creates more questions than answers, but it’s a real temptation particularly as visualisation programs become easier to use. Here’s another example of how being overly complex can lose the message and the audience. The infographic shows all the companies owned by Disney worldwide, worth over $200 billion. The resolution and general design elements make it difficult to read or follow.

data visualisation too complex

Source: Rigorous Themes

There’s a better way to present data, however, and it boils down to following a few best practices and aiming for simplicity.

The Power of Simplicity

It’s easy to create an attractive visualisation with a quick upload of the data and a few clicks of the mouse. Unfortunately, jumping straight into this process without much thought isn’t the ideal way to go about it.

Before you start creating any charts or playing around with any tools, there is need for some thought and understanding about the data, what it means, and what you hope to communicate. Who is the audience and what is most important to them? Every presentation is granted a limited space and time, so sticking to the main objective helps to keep you on track.

Once you know your mission and are clear of the objectives, you can move on to choosing an effective visual. There are so many chart options for both qualitative and quantitative datasets. It might be useful to try out a few different types if you are not getting a good fit, but always ensure that you are sticking to the message.

Below is an example of a simple, yet effective chart. There is a clear title and legend and a dash of color to highlight the data for three countries.

 data visualisation simplicity
Source: Datawrapper

The best kinds of data visualisations include charts that are simple and easy to understand. It shouldn’t take your audience too long to figure out what the chart means and why it matters.

There are a few principles of simple chart design that can help you produce an effective visualisation. We’ve touched on some of these already, but here is a summary to keep you on track:

  1. Understand your audience and create your data visualisation with them in mind.
  2. Pick the right chart for the data you have.
  3. Add context to your chart to maximize the audience’s understanding and appreciation of the data.
  4. Make the visualisation simple enough to digest.

A simple visualisation is not synonymous with a boring one. There are so many chart types to choose from, including a lot of interesting and unconventional ones that are sure to spark your audience’s attention. That being said, the data type and message you are communicating should guide you to the right chart to use. If a simple line chart, bar graph, or scatterplot are the best fit for the data, then you are better of picking one of these and adding effective chart design elements, labels, and contextualization to enhance your message.

Conclusion: Keep it Simple, Stupid

At the end of the day, the impact of any data visualisation is seen by whether it did justice to the data and was easy to grasp and meaningful to the audience. Starting with this end goal in mind, anyone can craft a visually appealing chart that is easy to understand as well. While complexity may be tempting, simplicity is the key to successful data visualisation.

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