Top 5 data visualisation tools you need to know in 2024

These days, having a good grasp on data visualisation is important to make complex information accessible and engaging to various stakeholders.

With the right tools, raw data can transform into clear, insightful visuals that tell a story, reveal trends that may otherwise go unnoticed, and lead to informed decision-making.

Here, we’ll dive into the top five data visualisation tools for 2024 that you’ll want to explore, whether you’re a seasoned data pro or a newcomer looking to bring data to life.

But first, let’s look at what you need to know before embarking on your data visualisation journey. 

What is data visualisation?

Data visualisation is all about turning raw data into visual stories, using charts, graphs, maps, and dashboards to make complex information easy to understand at a glance. Think of it as the art and science of making data visually accessible so people can spot patterns, trends, and insights quickly.

Data visualisation isn’t just for analysts and data scientists, either. It’s a tool that everyone can use. Whether you’re a business manager, a marketer or an educator, you can leverage it to make better decisions, communicate insights, and share information in a way that clicks. Ultimately, good data visualisation lets the data tell its own story, helping us see the big picture at a glance and dive into details as needed.

How to choose the right data visualisation tool for you

Choosing the ideal data visualisation tool depends on understanding your unique requirements and aligning those with the capabilities of each tool.

When selecting a data visualisation tool, consider the following factors:

• Budget: Figure out your budget for data visualisation tools, as they range widely in cost. Consider if a subscription or one-time purchase best fits your financial goals, and don’t forget to factor in any potential costs for training, maintenance, or upgrades.
• Data complexity: Assess the complexity of the data you’ll be working with. For simple reporting, a straightforward tool may be sufficient, but if you’re working with large, complex datasets, or need advanced analytics (like predictive modelling or AI-driven insights), you’ll likely need a tool that offers more robust data processing and visualisation capabilities.
• Integration needs: Look at how easily a tool integrates with your current data sources and software ecosystem. This is especially important if you’re using multiple platforms for data storage, CRM, marketing, or project management. Seamless integration allows for efficient data flows and reduces the time and effort needed to consolidate data.
• User skill level: Consider the technical expertise within your team. If team members are less experienced with data tools, prioritise a user-friendly interface with drag-and-drop functionality and built-in templates such as Tableau. For teams with technical expertise, more advanced tools with customisable features and in-depth functionality might be a better fit.
• Collaboration: If multiple team members will be working with the data or presenting insights, look for tools that allow for easy sharing, collaboration, and permission settings. Tools with cloud-based dashboards and real-time collaboration features can enhance team efficiency and streamline reporting processes.