Introduction to data visualisation

Data is everywhere. Over 90% of the world’s data has been created in the last 2 years alone and at the start of 2020 that was clocked at approximately 44 zettabytes of data swirling around our digital world. That’s a lot of data to try and make sense of.

What is Data Visualisation?

Data visualisation is the visual representation of information and data, and it allows us to turn very complex data into compelling, accessible, and understandable visualisations using a variety of graphic output such as maps, charts and infographics.

What are the Benefits of Data Visualisation?

As humans we process and store visual data better than any other type of data. In fact the human brain can process visual content 60 000 times faster than text. It makes sense then that as humans we find accessing and digesting data through visualisations easier than we would through tables or text documents.

Data visualisation tells a story. It brings data to life. It allows us to drive actions and decisions and spot patterns, trends, and outliers.

What could be presented as an impenetrable spreadsheet can be visualised in a way that people can understand. It makes data accessible.

And data visualisation is not new. For centuries it has and continues to be used as an important tool to report on some of the most important stories and subjects in our history.

Whether its mapping our landscape to help ward off the threat of invasion or reporting on the outbreak of Covid-19 data visualisation has informed and educated for many years.

Common Types of Data Visualisation

Data and visualisation need to work together. It’s a delicate balance between form and function and there is a real skill in combining data analysis alongside great storytelling. Picking the right type of visualisation is imperative to conveying the story of your data. To find out more about the different types of data visualisation commonly used today then please click here.

Data visualisation is the most important step when telling a story with data. The way we present our findings is fundamental to the decisions and observations that can then be drawn from it.

It makes data accessible. It makes data make sense.

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