Data visualisation and data flow designs: Tips for creative visualisation.
Summary/Overview
Don’t let data tie your clients and colleagues in knots – just break it down with graphs, charts, maps and plots. By using data visualisation tools, you can take big concepts and make them understandable at a glance. Forget wasting time on explanations, let your data talk for itself.
Discover more about data visualisation and learn how to share data that’s digestible. Get free examples and templates to optimise your reports with Adobe Express today.
What is data visualisation?
Data visualisation is when you represent information, data and statistics visually – in graphs, charts and infographics. It helps make things easier to understand and explain, especially if there’s a lot of data to process. It’s a bit like show, don’t tell – and there’s no understating how satisfying it feels to make a good graph.
Sometimes with data, you just need to get to the point. Percentages and statistics are great – but data visualisation and design allows you to share your analysis at a glance. You don’t want to get lost in the jargon – by using graphics you can represent data in a concise and understandable format.
For example, if you’re trying to communicate complex data points to key stakeholders, sharing a spreadsheet report can be time consuming and confusing. By converting key data into graphics, you can share the information you need in a streamlined presentation.
The benefits of good data design.
So, you know what data visualisation is – but it’s important to understand the advantages of good data design. Beyond being pretty on the page or a PowerPoint presentation, data visualisation allows you to:
Spot trends and patterns.
It’s easier to spot patterns in graphics than by parsing through data sets. Because the data is provided in a graphic format, anomalies stand out without the need to interrogate the numbers.
Facilitate decision-making.
By representing your data in a visual format, you can make decisions faster. Don’t get bogged down in information-heavy graphs, make data clear and readable at a glance to make the decisions you need.
Tell stories.
Good data is accessible data. By turning it into an understandable format, it removes the noise of excess information and provides a clear story.
Good data design can turn bulk data into a narrative that can be understood step-by-step. This can be especially important when sharing data to non-technical audiences or trying to justify or explain data.
Understand data.
Take complex information and make it digestible. By reducing information into graphics, you can read data quickly, regardless of your experience with spreadsheets or other data sets. This makes information easier to work with and refer to.
Improved retention.
Ever seen a room collectively glaze over without the right stimulus? Good data design can engage people and help them follow the information being shared. This can lead to better engagement – plus, interpreting data visually is a great communication tool.
Explore data visualisation with our editable examples.
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Different types of data visualisation.
You might now be ready to start plotting, mapping and charting. Before you do, it’s worth learning about the different ways to represent data.
Here are some data visualisation tools and how they’re best used:
Charts (bar, line, graph).
The reliable bar chart and line graph – some of the most widely used (and accessible) forms of data visualisation. These can be clear ways to compare values – for example, when allocating budget to different departments. However, they can also be used to track changes or even show rankings or deviations in data.
Not sure where to start? Explore some of our top graph and chart examples.
Plots (bubble, scatter, box).
Plots can demonstrate how data is distributed. They help you get a sense of data skew and symmetry – that means outliers are easy to detect. They can also illustrate how data is distributed, which includes minimum and maximum values as well as medians, quartiles and so on.
Maps (heat, tree).
Maps give you a spatial perspective on data, helping you to identify patterns. A colour-coded heat map can demonstrate change over time, but may not be as accurate as something like a line graph. However, they can be fantastic at quickly demonstrating the broad-strokes of a data set. Treemaps are similar, but illustrate things in a hierarchical structure.
Diagrams.
With the right visual aids, diagrams can provide bullet-point-style snapshots of data and outcomes. They can be an effective way of sharing important points of information. However, poorly designed diagrams can be confusing or misrepresentative.
Tables.
Tables are one of the most common forms of data visualisation – and for good reason. They allow users to quickly compare and understand patterns or relationships in the data provided. They’re clearly labelled and can be easily filtered, even by people with little experience. However, they have limitations on the types of information they can share.
Infographics.
Infographics combine a number of data visualisation methods, and are an excellent way to share a story of multiple data sets. Not only do they simplify complex data, they illustrate an engaging and understandable narrative when used correctly.
Learn more about infographics with Adobe Express.
Top tips for effective data design.
Good data design isn’t always as easy as getting out your marker and drawing a graph. Before you get creative with graphics, try to consider these top tips for effective data design.
Choose the right data visualisation method for your needs.
While data visualisation tools can bring your data to life, you need to choose them carefully. Good data design is about selecting the right tool for the job. Try to ask yourself, ‘What is this data trying to show?’, and then think about the best method to share that information, rather than try to make an approach fit.
Use colour and size to help give context.
Colour can be used to distinguish different data sets – although you want to avoid using too many similar shades. Not only can it be used to distinguish the differences between data, but it can also give context.
For example, if you’re using a comparative bar chart, you could put last year’s results in a different colour in the background, to distinguish from the current year in the foreground.
Be careful and considerate with text.
Text provides initial context, but poorly labelled data design can be more confusing than it is helpful. You want the graphics to do the talking, but concise and considerate text can make your graphics readable at a glance.
Keep your design simple.
Overdesign can be a real problem, leading to clutter and clarity issues. Try not to overload your graphics. Instead,, consider if the chosen data visualisation tool is appropriate. You may need to try a different approach or separate your data sets if designs become complex.
Likewise, don’t add too many flourishes that could risk muddying your visuals – tempting as it may be. This can be especially important when collating data into a complex infographic.
Free data visualisation templates to help you get started.
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(To pull in manually curated templates if needed)
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(Horizontal/Vertical)
Width
(Full, Std, sixcols)
Limit
(number of templates to load each pagination. Min. 5)
Sort
Most Viewed
Rare & Original
Newest to Oldest
Oldest to Newest
Premium
(true, false, all) true or false will limit to premium only or free only.
Useful things to know.
What are some data visualisation examples?
Data visualisation is something that sounds advanced, but we may be a lot more familiar with it than we think. Examples of data visualisation methods include bar charts, pie charts, infographics and scatter plots.
What is the golden rule of data visualisation?
In three words, keep it simple. Always choose the cleanest, most concise, and easiest-to-understand ways to represent the information you’re trying to share.
What are data visualisation tools?
Data visualisation tools are a way to convert complex data into easy-to-read and understandable graphics. That may sound complex, but the most accessible of these examples are infographics, bar charts and pie charts.