Data Visualisation: The hidden power of turning raw data into compelling stories

In the business world, data is everything. It tells us what customers want, what they’re buying, and where they’re going. It reveals what’s working and what’s not. But data isn’t just for businesses – it can also be used to tell stories.

Data visualisation is the process of transforming raw data into visual stories that are easy to understand and interpret. When done well, data visualisations can be incredibly powerful. They can help us see patterns and trends that we wouldn’t be able to see otherwise.

In this article, we’re going to explore the hidden power of data visualisation. We’ll look at some examples of how data visualisation can be used to tell stories, and we’ll also learn some tips and tricks for creating your own data visualisations

What is data visualisation?

Data visualisation is the process of turning raw data into visual stories. It uses charts, graphs, maps, and other visuals to show relationships and patterns in data. Data visualisation can help make complex data more accessible and easier to understand.

By seeing the data visually, it is much easier to comprehend and draw insights from it. Data visualisation also helps detect trends and anomalies within the data which can be used to inform decisions. For example, a graph can be used to show how sales from different regions have changed over time, which can be used to adjust the marketing strategy.

Data visualisation can also be used to illustrate relationships between different sets of data, such as population and income, or customer behaviour and profitability. By viewing data as a visual story, it is easier to identify potential areas of improvement, consider new opportunities, and make informed decisions.

The benefits of data visualisation

Data visualisation enables us to make informed decisions quickly and accurately. It has a wide range of benefits for businesses, including:

  • Cost-effectiveness: Visualising data allows us to see patterns and trends that would be much more time-consuming to detect through traditional methods, thus reducing the time needed to make decisions.
  • Accuracy: Data visualisation makes it easier to spot trends and anomalies in data and draw accurate conclusions.
  • Improved communication: Data visualisations can effectively convey complex information and relationships that can be difficult to follow in text. The visuals also make it easier to share the data with stakeholders.
  • Improved customer interactions: With data visualisations, customer insights can be easier to identify, allowing businesses to respond faster to customer needs.
  • Enhanced innovation: By visualising data, businesses can identify opportunities for improvement and generate new ideas for products and services.
The power of storytelling

Storytelling is one of the most powerful techniques when it comes to data visualisation. By weaving data into stories, businesses can create compelling visuals that are easy to understand and share.

Whether you are a business leader, data analyst, or an engineer, the art of storytelling can help you to bring data to life. It can help you explain complex data to others and generate deeper insights.

Through storytelling, you can turn raw data points into an engaging narrative. This is an excellent way to engage stakeholders and promote data-driven decision-making.

So, how can you tell stories with data visualisations?

Firstly, prepare a story outline: Start by asking yourself what do you want to communicate, why is it important and to whom. Doing this will help you determine what type of visuals you need and provide a structure for your story.

Then, design visuals to capture the story: Choose visuals that are clear, legible, and visually appealing. Consider the colours, font, and layout and use symbols to draw attention to key points.

Finally, use visuals to illustrate the story: Incorporate visuals into your story to explain complex concepts and demonstrate patterns. Use visuals to create impact and show the relationships between different data points.

How to get started with data visualisation

Data visualisation can be intimidating but is really quite simple once you have a grasp of the basics. By following some simple steps and using the right visualisation tool, anyone can create convincing data visualisations quickly and easily.

Let’s look at the step-by-step process for creating data visualisations.

Collect data: The first step is to collect the data you want to visualise. This can be from an internal source or an external source.

Clean data: Clean the data from any inconsistencies and ensure it is consistent.

Process data: Process the data and transform it into a format suitable for visualisation.

Choose a visualisation tool: There are many different visualisation tools out there. Make sure to choose the one that most suits your needs.

Select the type of visualisation: There are many different types of visualisations you can use, so make sure to pick the one that best suits your data.

Present the data: Presenting the data is the last step in the process, and is key to unlocking the understanding and insights of the data.

By following these steps, even a beginner can create effective data visualisations quickly and effectively.

Get articles from our team of experts in your inbox Subscribe
Examples of data visualisation

There is a wide range of data visualisation techniques that can be used to represent data effectively and accurately. Here are some of the most popular examples:

1. Bar charts – These are the most common type of chart used to represent data. They are used when there is a need to compare multiple groups, categories, or data points. They are usually best for comparing the size or length of something.

2. Line graphs – Line graphs are used to represent changes over time, or changes in one variable. They show the relationship between two variables, usually one that changes over time and one that does not. 

3. Scatter Plots – Scatter plots are used to represent two sets of data points and the relationship between them. It is used to observe the correlation between two variables.

5. Heat Maps – Heat maps are used to represent data by using colour or size. They display quantitative data, or data points that are placed on a two-dimensional grid. They show how different values are distributed on a map.

Data visualisation is an important tool when it comes to understanding data. It can help make even immense amounts of data easier to understand and manipulate.

Tools for the job

When it comes to data visualisation, the tools used can make or break the final product. The right tools can make the data come alive, while the wrong ones can make the information difficult to interpret. Here are some options that can help turn data into stories:

1. Tableau – Tableau is a powerful data visualisation platform that supports the full spectrum of data visualisations. It is used by professionals in a variety of industries to bring their data to life.

2. Qlik – Qlik is a self-service data analysis and visualisation platform. It is used to explore data and gain valuable insights.

3. Microsoft Power BI – Power BI is a suite of business analytics tools used to analyse data and deliver insights. It helps users gain actionable insights from both structured and unstructured data.

4. – is an online data analysis and visualisation tool. It helps to create charts, graphs, and dashboards with drag-and-drop simplicity.

No matter which tool you choose, it is important to use the right one for the job. The right data visualisation tool can help you create powerful and compelling stories from your data.

To wrap things up

Once you’ve figured out the tools, structure, and the design, it’s time to wrap things up. It’s important to have a conclusion that ties up all the loose ends. Make sure to not only convey the main points but to also summarise the insights you have drawn from the data.

You should also be sure to double-check the accuracy of your data visualisations. Data visualisations are only useful if they are accurate. This includes ensuring that all the specific data points line up with the stated insights and assumptions.

It is also important to consider how data visualisation can be used in larger contexts. Data visualisations can be seen as pieces in a larger story, which can be helpful for understanding what the data itself means.

Finally, consider how to best utilise the data visualisations to your advantage. Data visualisations can be used in presentations, reports, websites, and blogs. They can also be shared on social media to highlight the work you’ve done.

Data visualisation is an ever-evolving art. By staying on top of the latest trends and technologies, you can leverage data visualisations to tell even more powerful stories.