Pocket Guide to Getting Started in Data Visualisation Using Graphs
Few things are more important to a business than quality data. In many cases, though, effectively analysing your data in order to draw valuable insights can be just as challenging as collecting the data in the first place.
To ensure that you are using your data to its full potential, data visualisation is key.
My name is Payman Taei. I am a Founder and CEO of Visme. When I was creating the conception of the company, my top priority goal was to focus on producing design tools that would help people create beautiful content.
Sounds simple, isn’t it?
Then I realised that people want not just to create eye-appealing content but be able to provide information visually. I saw a direct correlation between the information people spread and the data they want to share. That’s why I decided to break new ground and bend every effort to develop the tools that would be able to visualise data.
Here at Visme, it has taken years of hard work and understanding of how the process of data visualisation is important. If data can’t speak for itself, nobody will be able to get it to the full extent.
That’s why one of the core principles behind Visme is to help people understand difficult things much easier with the help of visual elements. And data is not the exception to the rule.
In this article, we’ll explore what data visualisation is, the benefits that it offers, and how to leverage data visualisation using custom graphs.
What is Data Visualisation?
Data visualisation is the process of organising and presenting your data in a way that makes it easier to understand and analyse. Data visualisation makes use of visual elements such as charts, graphs, maps, and other data visualisation tools in order to create a visual representation of your data. This makes presenting that data to an audience more efficient in addition to making it more efficient for you and your team to analyse it for key insights.
Why is Data Visualisation Important?
Human beings are visual creatures. When you combine this with the fact that raw data is most often messy, unorganised, and quite difficult to analyse, it becomes essential to organise and present your data in a clean and visually appealing manner. If you are presenting important data to an audience of potential clients, for example, showing them a long list of unorganised numbers isn’t likely to make much of an impression. Organising the data into a graph or chart, however, makes it easy for them to understand at a glance what the data is saying.
In addition to making your data more presentable, data visualisation makes your data easier to analyse as well. Drawing insights from raw data is often a real challenge and is almost always a time-consuming and inefficient process. Organising your data via data visualisation techniques, though, makes whatever insights that data has to give much easier to spot.
Data Visualisation Best Practices
There are a number of best practices that will help you make the most of data visualisation. This includes practices such as:
1) Organise Your Data
Before your data can be represented visually, it needs to be properly organised. Let’s say, for example, that you have collected data on average customer spending. When that data comes in, it’s going to be a jumble of unorganised numbers. In this example, listing those numbers from lowest to highest would be one way to organise your dataset in a way that will make it easier to present.
2) Clean Your Data
Data cleaning is the process of filtering out any anomalies or inaccuracies that might be found in your dataset. Going back to our previous example, let’s assume that you had a customer who spent an incredibly large amount of money with your company that is many times more than your next biggest customer. You determine that this particular customer is an anomaly for your company that isn’t likely to be repeated in the future. Even though their data point is true and accurate, removing it from your dataset will give you a more meaningful reflection of what you can expect your company’s average customer spend to be moving forward. While you don’t want to be cavalier with your data and veer into the territory of massaging it for desired results, data cleaning is a wholly acceptable and necessary process that even scientific studies employ.
3) Select the Right Chart
When it comes time to present your data visually, there is a wide range of charts and graphs that you will have available to choose from – and each type comes with its own unique set of advantages. Line graphs, for example, are ideal for displaying patterns over time as well as displaying the correlation between two or more variables. Bar graphs, meanwhile, are better suited for comparing the results of numerous groups. Choosing the right chart for your data is an essential step if you want to ensure that the data’s key insights are easily understandable.
4) Label Your Chart
Charts and graphs make it easy to identify data patterns, but to communicate specific values you will need to make use of effective labelling. In most cases, simply including numbers along the X and Y axes of your chart is enough to make the specific values of your data easily evident. For charts that don’t include X and Y axes such as pie charts and heat maps, though, you may have to get a little more creative with your labelling strategy.
5) Highlight Important Points
Data visualisation is all about making it as easy as possible for your audience to understand the key points that your data is communicating. While formatting your data into a well-organised and properly labelled chart will go a long way toward accomplishing this purpose, you can go one step farther by emphasising important points on the chart. There are several ways to highlight a point of emphasis in your data, including symbols, small blocks of text, and contrasting colours.
Creating a Data Visualisation Graph
As you’ve probably noticed, graphs play a vital role in the data visualisation process – and the ability to easily create a custom graph that represents your data is something that can make your data visualisation process much more effective and time-efficient. At Visme, we’ve made it easier than ever before for you to create a fully customised graph of any type using our online graph maker. This simple to use tool enables you to create custom bar graphs, pie charts, flowcharts, diagrams, line graphs, histograms, and everything in between using straightforward point and click commands. To help you jumpstart the process of creating your custom graph, we also offer a wide range of professional templates that can serve as a beneficial starting point for your data visualisation needs. If you would like to present your data using a graph that is professional and attractive yet one that takes only a matter of minutes to create, be sure to give our helpful graph maker a try!