Best Data Visualisation Tools for Data Enthusiasts 2024

Summary: In 2024, data visualisation tools are essential for data enthusiasts looking to present insights effectively. This blog explores the best tools available, highlighting their features, usability, and unique benefits. From user-friendly interfaces to advanced analytics capabilities, these tools empower users to create impactful visualisations that enhance data storytelling and facilitate better decision-making.

Introduction

In many operations, the value of data has changed dramatically in recent years. For example, companies can now track the location of their vehicles and goods at any time, in real time. This was not possible a few years ago, and with data visualisation tools, you can easily convert the information into a more comprehensive and understandable picture.

There are many ways to effectively communicate data to an audience, but one of the most efficient ways to do so is to use data visualisation. With the help of these tools, it becomes easier for a Data Scientist to unfold the information hidden behind complex data and convey the same in a simplified manner.

Some common ways to visualise data include bar charts, line graphs, and scatter plots. It is important to choose the right visualisation method for the data being analysed and the question being asked.

What is Data Visualisation?

Data visualisation is the process of transforming data into a graphical format.  It helps in creating visual representations of data to make it easier to understand and draw inferences. It can be done using a variety of methods and tools, including charts, graphs, and maps. 

This allows people to quickly see patterns and trends in data. Several benefits of using data visualisation tools like simplifying complex data make it easier even for a technically night person to understand the information hidden in the data as well as present it in a more effective manner.

What are Data Visualisation Tools?

Data visualisation simplifies the representation of data and data visualisation tools play an integral role in this. These tools are designed to assess the data, derive useful inferences, and make it more relevant to the user.

When you are dealing with voluminous data, manual assessment is challenging and can be misleading sometimes, so you have the best data visualisation tools that simplify the process for the user. 

Key benefits of using top data visualisation tools:

• Helping to make sense of large and complex data sets
• Allowing for the identification of patterns, trends, and relationships
• Facilitating communication and understanding among team members
• Supporting decision-making
• Improving efficiency and productivity

What’s Common Among all the Data Visualisation Tools?

Although there are different Data Science tools their prime objective is the same and that is to unfold the meaning hidden behind complex data.

Hence all these tools have one thing in common, which is their objective to unveil the information and present it in a comprehensible manner. No matter which tool you choose, data visualisation can be a powerful way to see and understand data.

Data visualisation tools convert the information into graphs, charts, or other visual representations. Data Scientists use these tools to create static and non-static visualisation. Static visualisations are images generated from data that do not change when the data changes. Interactive visualisations are visualisations that change when the data changes.

Top Data visualisation Tool List

There are many different data visualisation tools available. Some data visualisation tools are designed for specific types of data, while others are designed to be more general. Data visualisation tools are also designed to be used with specific software applications.

Tableau

It is an online data visualisation software application that can be used to create a variety of static and interactive visualisations. Tableau includes a number of features for visualising data. It is a business intelligence tool that helps organisations visualise and analyse their data. It offers a variety of features and benefits, but also has some drawbacks.

 Key features of tableau

• A tabular format for data
• Can be used to present information in a more organised and readable way
• Allows for easy comparison of data
• Can be used to spot trends and patterns

Pros:

• It offers a variety of features and benefits
• Helps organisations visualise and analyse their data
• Can be used to create dashboards and reports -Is easy to use and learn

Cons:

• It can be expensive
• Requires a good understanding of data to be used effectively
• May not be suitable for all organisations

Google Sheets

Google Sheets is a spreadsheet application that runs on the web. It is a part of the Google Docs suite of productivity tools, including Google Docs and Google Slides. Google sheets can be used for a variety of purposes, such as creating a budget, tracking expenses, and organising data.

 Key features of Google Sheets

• Create and edit spreadsheets directly in your web browser
• Sheets automatically save your work as you type
• Create, edit, and collaborate with others on spreadsheets from your computer, phone, or tablet
• Access, create, and edit your spreadsheets wherever you go — from your phone, tablet, or computer
• Get stuff done anytime, anywhere with Sheets

 Pros

• Easy to use
• Familiar interface
• Collaborative

Cons

• Limited features and customization options
• No offline access

Microsoft Excel

Excel is a spreadsheet application that is part of the Microsoft Office suite of productivity applications. Excel can be used to store, organise, and analyse data.

There are many ways to use Excel as a data visualisation tool. One way is to use the built-in charts and graphs to create visualisations. Another way is to use the data in Excel to create custom visuals using the Visual Basic for Applications (VBA) programming language.

 Key features of Microsoft Excel

• The user can store, organise, and analyse data.

• It comes with built-in features that make it easy to enter and manipulate data.

• This data visualisation tool is loaded with powerful data analysis features that can be used to discover trends and relationships in data.

• Excel is a versatile program that can be used for various tasks, from simple data entry to complex data analysis.

Pros:

• Very versatile and can be used for a variety of purposes
• Can be customised to suit individual needs
• Allows for complex data analysis and manipulation
• Can be integrated with other software programs

Cons

• Can be difficult to learn and use
• May be slow on older computers
• Some features may be locked behind a paywall

Infogram

Infogram is an easy-to-use, cloud-based tool that lets you create stunning infographics, share them on social media, and embed them on your website.

It offers an extensive library of templates to help you get started, and you can customise your design to fit your brand. You can also access data from over 500 data sources, including Google Sheets, Excel, and CSV files.

Infogram is a data visualisation tool for free use, but a paid plan gives you access to more features, including custom branding and extended data storage.

Key features of Infogram

• Infogram is a free online tool that allows users to create interactive charts, maps, and infographics.
• It has many features that allow users to customise their charts and infographics, including the ability to add videos, images, and links.
• You can take the paid subscription to access more features, like creating private charts and infographics and downloading high-resolution images.

Pros: 

• Free to use
• Many customization options
• Can add videos, images, and links
• Paid subscription gives access to more features
• Includes a wide range of templates and charts
• Features an easy-to-use drag-and-drop interface

Cons:

• Limited features for free users
• Paid subscription can be expensive

ChartBlocks

ChartBlocks is a cloud-based charting tool that allows users to create, share, and embed interactive charts and graphs. It offers a free and paid plan, with the paid plan offering more features and options.

 Key features of ChartBlocks:

• ChartBlocks is designed to be easy to use, even for those with no prior experience in creating charts and graphs.
• It is flexible enough to allow users to create a wide variety of charts and graphs.
• One can easily customise using this tool, thus, it allows users to change the look and feel of their charts and graphs.
• ChartBlocks charts and graphs can be exported to a variety of formats, including PNG, JPEG, and PDF.

Pros:

• Easy to use
• Can create charts and graphs without any coding
• Free plan available
• Can share charts and graphs online or embed them on websites

Cons:

• Limited features and options on the free plan
• The paid plan is required to unlock all features and options

Datawrapper

Datawrapper is a tool for creating interactive charts and maps. It lets you upload your data and create a visualisation, which you can embed on your website or blog. The visualisations are responsive, meaning they will resize to fit the containing element’s width.

Datawrapper is free to use and open source. It has a paid version with more features, but the free version is more than adequate for most uses.

It offers a wide range of visualisation types, including bar charts, line charts, pie charts, scatter plots, and more. This makes it easy to find the right visualisation for your data.

There is no fuss when it comes to using this software. Even for users unfamiliar with data visualisation. The interface is intuitive, and it is easy to create a visualisation.

Key features of Datawrapper

• It allows the user to share visualisation via email, social media, or embedded on a website or blog.
• Ease of customization is yet another feature that gives the user leverage to create output as per specific requirements.
• Datawrapper is a very affordable option for data visualisation, with plans starting at just $9 per month.

 Pros:

• The visualisations are stunning and interactive.
• DataWrapper makes it easy to upload data from Excel, Google Sheets, and CSV files.
• Embed visualisation on websites and blogs.
• DataWrapper offers a free plan for up to five visualisations per month.
• Paid plans start at $19 per month and include unlimited visualisations.
• The user can integrate it with Tableau, Google Analytics, and other data visualisation tools.

Cons:

• Datawrapper might restrict advanced customization options for fonts, colors, and chart elements.
• Being open-source, there might be potential security concerns regarding data handling, especially for sensitive information.
• While simple charts are straightforward, creating complex visualisations might require additional effort and understanding.

Polymaps 

If you are looking for the best data visualisation tools that can give you access to create charts, and maps then following maps is one of the best options.

It is a free JavaScript library. Polymaps provides a speedy display of multi-zoom datasets over maps of arbitrary shape and size. Various plug-in tile sources are available, and the library is compatible with a range of GIS servers.

 The library is designed to be small and simple, yet still provide a powerful API. The library focuses on providing a basic set of features, so it does not include all of the bells and whistles that you find in other mapping libraries.

 Some of the features of Polymaps include:

• It supports multiple map types (Google Maps, Bing Maps, etc.)
• Polymaps is compatible with multiple data formats (KML, GeoJSON, etc.)
• It supports multiple projection types (Mercator, Orthographic, etc.)
• It has a simple API for creating and interacting with maps

Pros:

• Allows you to display data on a map in a very visually appealing way
• Is interactive- users can hover over data points to see more information
• You can use it to display a variety of data types

 Cons:

• May be difficult to set up if you are not familiar with coding
• Limited to display data that can be mapped geographically

Grafana

Grafana is a data visualisation tool that allows you to create dashboards and charts to visualise data from a variety of data sources. It is one of the best data visualisation tools open source  that is distributed on the AGPL 3.0 licence

Grafana is a data visualisation and monitoring solution that allows you to query, visualise and alert on data collected in Prometheus. It can also be configured to take data directly from other data sources, such as an InfluxDB database.

Grafana is a popular open-source visualisation tool that can be used on top of a variety of different data stores but is most commonly used together with Graphite, InfluxDB, Prometheus, Elasticsearch, and Logz.io.

Grafana allows you to query, visualise, alert, and understand your metrics no matter where they are stored. Create, explore, and share dashboards with your team and foster a data-driven culture.

 Key features of Grafana

• A rich set of panel types including graph, table, gauge, heatmap, and more
• An intuitive and powerful query editor
• The ability to combine multiple data sources on the same dashboard
• A flexible and responsive layout that adapts to any screen size
• A built-in alerting engine with email, Slack, and PagerDuty notifications
• An easily extensible plugin architecture
• Some of the big names in the business world Cisco, Dell, eBay, IBM, Microsoft, Paypal, and Slack rely on Grafana

 Pros

• Grafana is open-source and free
• It is easy to install
• It has a large user community
• There are many plugins available
• Grafana is highly customizable
• The user can  share the dashboard 

 Cons

• Grafana dashboards can be difficult to understand for those who are not familiar with them
• It requires a fair amount of setup and configuration
• It is not compatible with a few monitoring tools, so there may be less support available

Fusioncharts

FusionCharts is a JavaScript charting library that enables you to create interactive charts, dashboards, and data visualisations for your web applications.

FusionChart is a cross-platform and cross-browser charting solution.  One can create interactive charts for web, mobile, and desktop applications using it. It offers a wide range of features that make it a powerful and flexible tool for data visualisation.

Key features of FusionChart: 

• FusionChart can be used to visualise data in various ways with the help of interactive and customizable chart types 
• It has a rich API which allows developers to create custom applications and integrations.
• It offers cross-platform and cross-browser compatibility.
• FusionChart is compatible with many platforms and browsers, making it a versatile solution for data visualisation.
• FusionChart can be used with various data sources, including relational databases, XML, JSON, and CSV files.
• It offers a flexible licensing model that allows developers to choose the features and functionality they need.

 Pros

• It is a very powerful and flexible tool that can create various charts and graphs.
• Using FusionChart is easy
• A wise array of options and settings allow you to customise the appearance of your charts.
• You can use the free trial to try out the software

 Cons

• It can be expensive
• Incompatibility with all web browsers.
• Using this tool is a bit challenging task 

How Data Visualisation Tools Can Boost Your Career?

Data visualisation has come a long way in the last few years. These tools help the Data Scientist and analyst to easily turn data into information and pictorial representation which is better decision-making. However, data visualisation is not just for analysts and managers. In today’s data-driven world, data visualisation is a valuable skill for anyone who wants to further their career.

Data visualisation is a key tool for Data Scientists, allowing them to effectively communicate their findings to both technical and non-technical audiences. By visualizing data, Data Scientists can better understand complex relationships and patterns, identify trends and outliers, and communicate their findings in a more accessible and engaging way.

Read More ?? Data visualisations in Python and R

Wrapping it up !!!

The purpose of data visualisation is to communicate information effectively through graphical means or pictorial representation. It is one of the key components of Data Science and finds wider usability by data analysts and scientists to gain insights into their data. Some common types of data visualisations include line graphs, bar charts, scatter plots, and heat maps.

Data visualisation is an important tool for Data Science because it allows data analysts and scientists to quickly and easily gain insights into their data. It also allows them to communicate their findings to others clearly and effectively.

So, if you are keen to become a Data Scientist and are exploring the best big data applications, excelling in using the top data visualisation tools is paramount. 

Frequently Asked Questions

What is Data visualisation?

There is no one answer to this question as data visualisation can mean different things to different people. Still, data visualisation generally refers to taking data and representing it in a graphical or visual format. You can do this in various ways, such as through charts, graphs, maps, or other visual representations.

Why is Data Visualisation so Important?

Data visualisation assists in a better understanding of the data.  Graphically representing hence, data makes it easier to understand patterns that may otherwise skip our eyes. 

What Should I Look for in a Data Visualisation Tool?

A data visualisation tool should have a range of features that allow you to manipulate and present data effectively and efficiently. Some of the key features to look for include:

• The user can load data from a variety of sources
• It allows the user to manipulate data to create custom visualisations
• One can share the visualisations with others
• Ease of sharing visualisations for use in other applications
• Customization features that allow the user to meet your specific needs
• The ability to interact with visualisations to gain deeper insights into the data
• One can create dynamic and interactive visualisations
• Easily integrate visualisations into other applications