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Top 10 Best Data Visualization Tools in 2022

Posted in Data Science
Data Visualization Tools

Sometimes, raw data is enough for people to draw insights and conclusions from. However, this is not always the case, especially when it comes to massive data sets with overwhelming amounts of information. Most people would likely struggle with understanding raw data when there’s no context or additional information provided. Massively increase the amount of data, and drawing insights pretty much becomes impossible. This is where data visualization tools come in.

Data visualization tools allow information to be presented in a much simpler and much more understandable way. They are used across all sorts of industries and sectors and can be truly impactful in helping people make better data-driven decisions.

Want to learn more about the best data visualization platforms and software? Read on to find out more!

Best Data Visualization Software

  • HighCharts
  • D3.js
  • Echarts
  • Vega
  • FineReport
  • Tableau
  • PowerBI
  • Leaflet
  • Deck.gl
  • Sisense

What is Data Visualization? [Definition]

Data visualization provides actionable information by representing significant amounts of data visually. This data science process developed by Joe Blitzstein involves various aspects, including information technology, statistical analysis, graphics, interaction, and more. 

Data visualization is a component of the broader discipline of data presentation architecture (DPA), which identifies, locates, manipulates, formats, and presents data in the most effective way possible.

In essence, data visualization is a process used to graphically represent data in various forms, including:

  • Pie charts
  • Gantt charts
  • Bar charts
  • Histograms
  • Box-and-whisker plots
  • Heat maps
  • Waterfall charts
  • Scatter plots
  • Area charts
  • Maps
  • Infographics

Why is Data Visualization Important?

Data that is presented visually is much easier for viewers to understand. And because they can understand the data well, they can also analyze it, allowing them to draw conclusions and actionable insights. These insights can be helpful in making impactful data-driven decisions.

Data visualization can be an effective way of ensuring that data is more easily accessible throughout any organization. In business, data visualization can help empower stakeholders to make more financially-sound decisions or give employees concrete information to help them in their day-to-day work processes.

Of course, data visualization can also help outside of an organization. In fact, visualized data is often how any organization communicates its data to outsiders, such as potential customers, media, stakeholders, regulatory agents, investors, or the public in general.

Many organizations understand how truly powerful a tool data visualization can be. As such, many companies are now hiring professionals specifically proficient in it alongside many other skills in data science. You’ll also now see many courses and degree specializations delving into the niche that is data visualization.

Data Visualization Technology

Data visualization has existed for many, many years, as evidenced by the various manual methods available. Before visualizing software came to be, many were already creating charts, graphs, and more using tools such as pen, paper, and various plotting materials.

Today, there are different techniques used for visualizing data. Some of them can be done manually, while others rely more on computers and other tools that can do them automatically. In data visualization, you’ll see things like the below in action:

  • Basic mathematics: trigonometric function, the geometric algorithm, and linear algebra
  • Engineering algorithms: basic algorithms, standard layout algorithms, and statistical algorithms
  • Visual basis: visual coding, graphical interaction, and visual analysis
  • Design aesthetics: design principles, color, interaction, cognition, and aesthetic judgment
  • Graphics: Canvas, computational graphics, SVG, graph theory, and WebGL
  • Visualization solutions: correct use of charts and visualization of common business scenarios
  • Data analysis: data cleaning, data modeling, and statistics

What Are Data Visualization Tools?

Data visualization tools are programs or apps designed for the specific purpose of presenting data in a visual manner. Each tool may have different feature sets that can make them better for certain purposes than others. 

However, at their core, these tools all serve the purpose of allowing you to input datasets so you can visually manipulate them.

Big data visualization tools, like the ones listed below, can handle data sets that have data points in the millions. They can automate processes to make visualization far easier for the designer or data handler.

Many tools are bundled with templates that users can take advantage of for quick and easy data visualization.

Top Data Visualization Tools [2022]

Now that we’ve discussed data visualization and the ways to make data much more digestible, let’s take a closer look at the top 10 tools available today.

1. HighCharts

HighCharts first came out in 2009 after it was mainly created by Torstein Hønsi, who first thought of and demonstrated the idea in 2006. Over a decade later, HighCharts by Highsoft is now one of the best database visualization tools available. HighCharts is not an open-sourced product as its license is proprietary. However, you can use it for free if your intended use is personal and non-commercial. If you’d like to use Highcharts in commercial applications, you’ll need to pay for a license.

HighCharts is frequently included in lists of the best JavaScript libraries for charting, and for good reason. It is a complete charting library written fully in JavaScript. As a tool that makes it much easier and more convenient to turn data into interactive charts, Highcharts can help you make information much easier to understand for anyone. This tool is mostly used on the web as it was designed to help enhance web apps by adding interactive charts.

With this tool, you can output data in various forms, including but not limited to spline charts, line charts, bar charts, area charts, pie charts, and more.

A sample chart made in HighCharts

Pros

  • Various charts are available with lots of options
  • Good documentation
  • Excellent browser support
  • Supports Y axes
  • Libraries of Highchart support microsoft.NET

Cons

  • Some complaints of support lacking and of people having to spend time on StackOverflow trying to figure out a bug

2. D3

D3 is actually short for something: Data-Driven Documents. D3.js is another library of JavaScript made for producing dynamic and highly interactive graphs and data visualizations within web browsers. It came out in 2011 as version 2.0.0, and as the successor to Protovis (another framework). Its version 4.0.0 came out in June of 2016, and it was during this version that D3.js switched from being a single library into a group of smaller modular JS libraries that you can use independently.

To use D3, you’d need to have at least some knowledge of JavaScript or access to someone who can help you out with the programming language. D3.js does what it does by using HTML5, CSS, and SVGs (scalable vector graphics). If you have no access to such an individual, you can always try one of the apps that allow you to use D3.js with no programming knowledge. NVD3 is an example of an app that allows anyone to create (reusable) charts using D3.js with no programming knowledge whatsoever.

Samples of scatterplot graphs created with D3.js

Pros

  • Powerful yet highly customizable
  • Documentation is available
  • Hands full control over to the developer
  • Wide range of charts available for use
  • Free

Cons

  • Requires you to have programming knowledge
  • As a free tool, D3.js does not offer as much support to users
  • Older browsers are not supported

3. Echarts

Echarts is a project initially created by Baidu in 2013. However, in 2018, the decision was made to enter Echarts into incubation at Apache. In 2021, Apache then announced that Echarts would be a top-level project or TLP at the organization. Today, nothing has changed in terms of how you can use this tool — Echarts remains an open-source and free-use visualization software despite being capable of enterprise-level charting work.

Echarts is a complete and fully open-source charting library for JavaScript. Unlike many other libraries, Echarts is actually highly compatible with various devices, making it the choice of developers who want to visualize data on PCs and mobile devices.

A sample created with Apache ECharts (formerly Baidu Echarts)

Pros

  • Free to use and easy to implement
  • Highly compatible with the majority of devices available today

Cons

  • Not flexible enough as compared to other chart libraries that are based on descriptive grammar
  • Customizing some of the more complex relational charts isn’t very straightforward

4. Vega

Vega, as well as Vega-Lite, are data visualization tools that implement grammar of graphics. Vega acts mostly as a lower-level language and typically has the same type of use case as D3.js. Vega-Lite, on the other hand, is on the opposite end of the spectrum, acting as a high-level language suited more towards exploring data rapidly.

The Vega GitHub Repository states that Vega is visualization grammar. It further explains that it is a declarative language used to create, save, and share interactive data visualizations in JSON formats. You can also generate views for the web via SVG or Canvas.

Samples of charts created with Vega

Pros

  • Users can create a variety of charts by combining Vega grammar
  • It is easy to use for its interactive interface

Cons

  • The grammar design is a bit complex
  • The cost of the process is high

5. FineReport

FineReport is another data visualization tool written in pure Java that just happens to be quite user-friendly thanks to its user interface. As an enterprise-level web reporting tool, you’ll be able to do some of the best data visualization available without ever having to code anything. In fact, FineReport’s “no-code development” design concept employs the simple and easy process of “drag-and-drop.” Needless to say, this tool is quite intuitive to use.

FineReport almost looks like Microsoft Excel and in a way, functions like it. Today, it’s used by more than 2,000,000 people in various industries like finance, information technology, government, manufacturing, aviation, energy, transportation, retail, and more.

A look into FineReport’s user interface and a sample chart

Pros

  • Easy to create complex reports by the data
  • Data entry is smart

Cons

  • Multiple data analysis is inconvenient
  • No recommendation of chart feature

6. Tableau

If you haven’t already heard of Tableau before, it’s actually one of the most popular tools for data viz currently available on the market. It’s incredibly popular mainly for two reasons — first, it is pretty easy to use with a pretty small learning curve and second, it’s quite powerfu. On top of that, it’s also capable of integrating with hundreds of different sources, allowing users to import their data and output all sorts of data visualization types like maps and charts.

Tableau is a tool owned by tech company Salesforce, and it currently has millions of community members and users at the enterprise level. It’s an incredibly convenient tool that allows you to create your data visualizations without coding while also providing the capability to do real-time collaboration.

Salesforce also makes its tool available for free in the form of Tableau Public. However, it’s important to note that using Tableau Public means any visualizations you create are going to be available for everyone. Only use Tableau Public if you are not working with sensitive or proprietary data.

Samples of Tableau’s data visualizations

Pros

  • Great visual image capabilities
  • This tool provides multiple information supply connections
  • User-friendly and intuitive
  • Free tool available

Cons

  • High cost and inflexible valuation
  • Security problems and poor after-sales support

7. Power BI

Power BI is a powerful data visualization tool offered by none other than Microsoft itself. It’s pretty easy to use and is quite intuitive to learn, so it is a good tool for less tech-savvy users. Power BI can be installed on-premise or deployed on cloud infrastructure. Microsoft’s tool is currently one of the best and most complete tools. It currently supports a ton of databases including Salesforce, Teradata, Oracle, PostgreSQL, Google Analytics, Azure, and much more.

As an enterprise-level tool, you can use Power BI to create effective visualizations that allows viewers to glean actionable insights that can help them make fast decisions. If you choose to use Power BI, you can create visualizations for viewing not just on the web but also on mobile.

You may find some people making comparisons between Power BI and Microsoft Excel. In a way, they are somewhat similar, but Power BI offers more functions and more effective data visualization features.

Thanks to its user-friendliness, Power BI is in the running for the best tool for data visualization for beginners.

A sample sales & returns data visualization created with Power BI

Pros

  • This tool has excellent affordability
  • Custom visualization and excel integration
  • Integrates easily with other applications
  • Good security
  • Compatible with other Microsoft Products

Cons

  • Tool interface is pretty crowded
  • Can’t work with multiple, varied datasets

8. Leaflet

Leaflet was created eleven years ago by Volodymyr Agafonkin. Release 1.8.0 of this JavaScript library just came out on April 18 of 2022.

Leaflet is one of the top open-source JS libraries specifically for making interactive maps that are user-friendly. Within Leaflet, you’ll find pretty much all of the mapping features you’ll need as a developer.

This JavaScript library was created with performance in mind, so you’ll find it’s designed to be quite simple and usable. It will work well on most major PC and mobile platforms. You can use various plugins to extend the functionality of this library as well.

Going to the Leaflet GitHub repository will show you that many of its sources and images are currently unavailable. It is unclear whether Leaflet is currently being maintained by its contributors.

A sample map data visualization created in Leaflet

Pros

  • You can use plugins
  • Source code is simple and readable
  • API is well-documented
  • Open source
  • Lightweight

Cons

  • Not so much support from contributors; Leaflet’s GitHub repository has many open issues 

9. deck.gl

If you are looking for a framework you can use for exploratory analysis of massive datasets, you can look to deck.gl. Deck.gl is powered by WebGL and uses a layered approach to visualizing data. It’s designed to make the process of high-performance visualization of substantial amounts of data much more simple all around.

You’ll notice that deck.gl mostly focuses on creating 3D map visualizations of data. It works standalone with no need for a base map. However, it also works well with other map providers including Google Maps. It’s highly customizable as well. The downside is, of course, that you need to know enough about WebGL to work with this tool.

It might come as a surprise but deck.gl is actually an open-source framework by a team of engineers at Uber. Yes, that Uber.

You can view a showcase of data visualizations created using deck.gl here

Pros

  • Easy to use if you know enough WebGL
  • High performance
  • A lot of documentation available

Cons

  • Cost issues
  • Poor BI capabilities
  • Requires knowledge of WebGL

10. Sisense

Sisense is an AI (artificial intelligence) driven software created for the purposes of business intelligence. It was created by a software company of the same name which was founded in Tel Aviv, Israel in 2004 and is now headquartered in New York, New York. Sisense also has a few other offices in locations like Scottsdale, Arizona and San Francisco, California.

Sisense is frequently recognized as one of the best agile tools for data visualization. It gives its users access to immediate data insights and analytics anytime and anywhere. This tool is capable of identifying key patterns in data while also being able to summarize any statistics found in the data. The instant analytics helps organizations make faster data-driven decisions.

An example of a Sisense dashboard

Pros

  • User-friendly and reliable user interface
  • Excellent support
  • Easy upgrades
  • Easy customization
  • Flexibile
  • Great for projects with huge datasets

Cons

  • Hard to manage and improve analytic cubes
  • Offers a limited type of visualizations

Best Data Visualization Tools: What Do They Have in Common?

When you look at each contender for the best data visualization tool, you’ll probably notice quite a few things that they have in common. Besides providing the capability to input datasets and manipulate them into visual output, the top tools have some overlapping features such as:

  • User-friendliness and general ease of use - As you might imagine, there are many visualization tools that can be incredibly complex. Such tools can be highly intimidating to approach and overwhelming to use, especially for beginners or those who aren’t particularly tech-tuned. The best tools will be easier to use and have plenty of documentation, tutorials, and support available for those challenged by the learning curve.
  • Capability to handle massive amounts of data - The best data vis tools can handle tons of data and can even work with multiple datasets to output a single visual representation.
  • Ability to output in various forms of visualization - The fact that there are many different ways to represent data graphically means that visualization tools should also have the ability to output in these different forms. The best tools will be able to output a vast array of graphs, charts, maps, and more. Some tools might even be able to represent data in an interactive way. Note that there are some tools specifically designed to output in only certain forms of visualization, and that doesn’t necessarily mean that they are bad. In fact, tools designed this way can be very good at presenting data in that particular manner.
  • Value proposition - Cost is always a factor in any purchase decision. As such, it only makes sense that the best tools offer value equal to the price they ask. Higher price tags aren’t necessarily a bad thing if the tool justifies the cost with its feature set.

If you’d like to learn more about data visualization but don’t quite know where to start, here are a few recommended courses on the subject:

  • Data Visualization with Tableau Specialization(Coursera) offered by the University of California Davis - This course on Coursera allows learners to figure out how to visualize business-related data using Salesforce-owned Tableau. As of writing, this program has already had over 100,000 enrollees.
  • Data Visualization Nanodegree by Udacity - Although this nanodegree from Udacity will cost you a fair bit of money, the certificate you earn at the end will be widely recognized by many employers around the world. With this program, you’ll learn how to combine visuals, data, and narratives. The program runs for an estimated four months and requires basic skills in both statistics and data analysis.
  • Data Science Visualization offered by Harvard University on edX- This course on edX is available entirely for free although upgrades are available at cost. The program will take an estimated eight weeks if you do an hour to two of learning each week, but as it is self-paced you can certainly finish much faster. This course teaches basic principles of data visualizations and how you can apply them using the open-source ggplot2.

Conclusion

Data visualization is something used across all sorts of industries and sectors. You’ll see it in business, health, and education, to name a few. You’ll also see a variety of data visualization tools that can make it much easier for you to present data in a simple, informative, and effective manner.

Because there are so many data visualization programs, it can be incredibly challenging to point out the single best one. The tools we’ve discussed above are widely used in various industries to help them solve problems and make better decisions all around.

Are you deciding on a tool to use? Or are you already using one but thinking about shifting to another? Either way, we hope that this list of the best data visualization tools in 2022 has helped!

Is there a tool you would like to see on this list? Feel free to tell us in a comment below!

Frequently Asked Questions

1. What is the easiest data visualization tool to use?

One of the easiest data visualization tools is Microsoft Excel, which has a variety of visualization methods and a relatively easy user interface. You can also try Microsoft’s Power BI or Google’s Data Studio.

2. What is the best free data visualization tool?

One of the best data visualization tools all around is Tableau Public, which does also happen to be available for free. Tableau Public allows users to make various interactive charts that let viewers take a deeper dive into the data presented.

3. Is Python a data visualization tool?

In a way, yes. Python has a few libraries used for plotting data, such as Matplotlib and Seaborn. These libraries have features that allow you to plot data and present information in a simple yet highly effective way. It’s not the easiest tool to use, but it can be very effective.

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Simran Kaur Arora

Simran Kaur Arora

Simran works at Hackr as a technical writer. The graduate in MS Computer Science from the well known CS hub, aka Silicon Valley, is also an editor of the website. She enjoys writing about any tech topic, including programming, algorithms, cloud, data science, and AI. Traveling, sketching, and gardening are the hobbies that interest her. View all posts by the Author

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