Advantages and Best Uses of Four Popular Data Visualization Tools Advantages and Best Uses of Four Popular Data Visualization Tools
Data visualization platforms vary widely in their capabilities, required skill sets, and uses. While some platforms are easy to use, they oftentimes can’t communicate... Advantages and Best Uses of Four Popular Data Visualization Tools

Data visualization platforms vary widely in their capabilities, required skill sets, and uses.

While some platforms are easy to use, they oftentimes can’t communicate complex, multivariable data the way that tools with a little more complexity can. Here, we compare four popular visualization programs and their advantages, disadvantages, and best uses. Among them are tools that do and do not require coding skills: Tableau, R, Plotly, and Infogram.

Tableau

Tableau is among the best-known and most widely used data visualization and analytics software with more than 78,000 user accounts on its paid desktop and free online platforms. Tableau allows users to create maps and a variety of charts with interactive hover, click, and filtering capabilities, and then present them together to communicate complex data or tell a story.

Advantages

  • After uploading or connecting their data to Tableau, users can drag and drop fields into various locations to explore interesting elements of the data. This makes it very easy and straightforward to visualize complex concepts and gain insight from them.
  • Tableau can handle hundreds of thousands or millions of rows of data and allows users to navigate many data fields simultaneously.
  • Tableau’s extensive interactivity elements mean users can easily make charts that allow others to explore the data for the conclusions they’re interested in.

Challenge

  • It can take a lot of time and training to learn how to utilize all of Tableau’s capabilities.

Best for users who…

Tableau is an ideal platform for general users who want to visualize large, multi-attribute datasets and use them to gain or share insights.

 

R

Many data analysts, storytellers, and data enthusiasts learn to program in R to expand their data visualization capabilities. The free and open source R programming language has a number of libraries like ggplot and plotly that allow users to create detailed visualizations with options for interactivity. At the same time, users can create statistical models and manipulate the data in the same place as they visualize it for a streamlined visualization and analysis process.

Advantages

  • There are a number of visualization libraries and extensive online resources on how to use those libraries, like this R-bloggers guide.
  • R code is reproducible and easy to export into various presentation formats, including PDFs and full websites.
  • R programmers can also visualize data in 3D models and multipanel charts.

Challenge

  • R is different than other popular coding languages in complex ways, and can be difficult for coders and non-coders alike to pick up on if they have no prior experience.

Best for users who…

R is a good tool for those who know how to code and want to use charts to accompany complex statistical analyses.

 

Plotly

Web-based data visualization tool Plotly is a powerful open source software that allows users to make interactive charts — either through its online graph maker or as a visualization library for coding languages Python, R, and JavaScript.

 

Advantages

  • Plotly is adaptable: In its simplest form, a user can plug in some numbers, select the type of chart they want to make, choose which variables they want to chart and customize through easy selection options. To kick it up a notch, users can manually adjust JSON settings or use Plotly as a programming library rather than using the online portal.
  • The software allows for some statistical analysis as well, including curve fitting and moving average analyses.
  • Plotly’s straightforward online platform enables complex visualization strategies, like subplots, data transformations and annotations, and has built-in instructions to complete these tasks.

Challenge

  • It can be difficult to visualize complex data or make complex, multi-field charts using Plotly’s online tool, and use of the Python, R and JavaScript libraries requires users to have coding ability.

When to use

Plotly is a good platform for all different kinds of users: From avid coders to those who just want to make simple charts, and especially for those who don’t know much or any code but are interested in learning.

Infogram

Infogram is an online data visualization platform that allows users to easily make infographics, reports, charts and maps with hover-over interaction and filtering capabilities. There is a free version that allows users to make charts that can be shared and embedded online, and paid versions with more capabilities, including the ability to export the charts.

Advantages

  • The platform has an easy and straightforward drag-and-drop editor, requiring little — if any — training.
  • Featuring ready-made templates and straightforward customization options, users can present data beautifully in a number of formats to fit its intended purpose, and can do so in minutes.
  • Paid versions of Infogram include team functionality, so multiple people can easily access and update charts.

Challenge

  • It can be difficult to present multiple fields on Infogram, making it more difficult to compare various data features to each other for more complex visualization and analysis.

When to use

Infogram is best for users who haven’t done much data visualization before and are interested in making simple but aesthetically pleasing charts.

Conclusion

There are free and paid data visualization tools for data enthusiasts at all skill levels. Those who start on platforms like Infogram can work their way up to more and more intricate ways of visualizing increasingly complex data.

Did we fail to include your preferred data visualization program in this breakdown? Let us know what platforms you want to learn more about.

Paxtyn Merten

Paxtyn Merten

Paxtyn is a student at Northeastern University studying journalism and data science.

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