The Best Data Visualization Tools

: Consuming large sets of data isn’t always straightforward. Sometimes, data sets are so large that it’s downright impossible to discern anything useful from them. That’s where data visualizations come in.

Creating data visualizations is rarely straightforward. It’s not as if designers can simply take a data set with thousands of entries and create a visualization from scratch. Sure, it’s possible, but who wants to spend dozens or hundreds of hours plotting dots on a scatter chart? That’s where data visualization tools come in.

What Are Data Visualization Tools?
Data visualization tools provide data visualization designers with an easier way to create visual representations of large data sets. When dealing with data sets that include hundreds of thousands or millions of data points, automating the process of creating a visualization, at least in part, makes a designer’s job significantly easier.

These data visualizations can then be used for a variety of purposes: dashboards, annual reports, sales and marketing materials, investor slide decks, and virtually anywhere else information needs to be interpreted immediately.

What Do the Best Data Visualization Tools Have in Common?
The best data visualization tools on the market have a few things in common. First is their ease of use. There are some incredibly complicated apps available for visualizing data. Some have excellent documentation and tutorials and are designed in ways that feel intuitive to the user. Others are lacking in those areas, eliminating them from any list of “best” tools, regardless of their other capabilities.

The best tools can also handle huge sets of data. In fact, the very best can even handle multiple sets of data in a single visualization.

The best tools also can output an array of different chart, graph, and map types. Most of the tools below can output both images and interactive graphs. There are exceptions to the variety of output criteria, though. Some data visualization tools focus on a specific type of chart or map and do it very well. Those tools also have a place among the “best” tools out there.

Finally, there are cost considerations. While a higher price tag doesn’t necessarily disqualify a tool, the higher price tag has to be justified in terms of better support, better features, and better overall value.

Data visualization example
This data visualization shows the Human Rights Protection index (from 1950 to 2014) and the Human Rights Violations index (in 2014) for 50 countries. (by Federica Fragapane)
Data Visualization Tools Comparison
There are dozens, if not hundreds, of applications, tools, and scripts available to create visualizations of large data sets. Many are very basic and have a lot of overlapping features.

But there are standouts that either have more capability for the types of visualizations they can create or are significantly easier to use than the other options out there.

Tableau (and Tableau Public)
Tableau has a variety of options available, including a desktop app, server and hosted online versions, and a free public option. There are hundreds of data import options available, from CSV files to Google Ads and Analytics data to Salesforce data.

Output options include multiple chart formats as well as mapping capability. That means designers can create color-coded maps that showcase geographically important data in a format that’s much easier to digest than a table or chart could ever be.

The public version of Tableau is free to use for anyone looking for a powerful way to create data visualizations that can be used in a variety of settings. From journalists to political junkies to those who just want to quantify the data of their own lives, there are tons of potential uses for Tableau Public. They have an extensive gallery of infographics and visualizations that have been created with the public version to serve as inspiration for those who are interested in creating their own.


Hundreds of data import options
Mapping capability
Free public version available
Lots of video tutorials to walk you through how to use Tableau

Non-free versions are expensive ($70/month/user for the Tableau Creator software)
Public version doesn’t allow you to keep data analyses private
Data Visualization Examples

Data visualization tools can be used for all kinds of projects
A data visualization of unique words used by three the Game of Thrones book series.

Data visualization examples: moose crashes in Maine
Data visualizations can make public safety data easier to digest.

Data visualization tools make it easy to create interactive visualizations
An interactive visualization of the highest-grossing actors of all time.
Bottom Line

Tableau is a great option for those who need to create maps in addition to other types of charts. Tableau Public is also a great option for anyone who wants to create public-facing visualizations.

Infogram is a fully-featured drag-and-drop visualization tool that allows even non-designers to create effective visualizations of data for marketing reports, infographics, social media posts, maps, dashboards, and more.

Finished visualizations can be exported into a number of formats: .PNG, .JPG, .GIF, .PDF, and .HTML. Interactive visualizations are also possible, perfect for embedding into websites or apps. Infogram also offers a WordPress plugin that makes embedding visualizations even easier for WordPress users.

Data visualization methods
Visualizations can make complex topics easy to understand.

Data visualization framework
Charts make data easier to compare, year-to-year.

Data visualization techniques: mapping
Maps are an excellent way to give a snapshot of worldwide data.
Bottom Line

Infogram is a great option for non-designers as well as designers. The drag-and-drop editor makes it easy to create professional-looking designs without a lot of visual design skill.

US-based full-time freelance UX designers wanted
ChartBlocks claims that data can be imported from “anywhere” using their API, including from live feeds. While they say that importing data from any source can be done in “just a few clicks,” it’s bound to be more complex than other apps that have automated modules or extensions for specific data sources.

The app allows for extensive customization of the final visualization created, and the chart building wizard helps users pick exactly the right data for their charts before importing the data.

Designers can create virtually any kind of chart, and the output is responsive—a big advantage for data visualization designers who want to embed charts into websites that are likely to be viewed on a variety of devices.

Information visualization tools make creating charts easier
Stacked graph charts are an effective way to compare and contrast data.

Fundamentals of data visualization: Simple charts can be the most effective
Scatter plots are a simple way to represent data trends.

Data visualization best practices: line charts
Line charts are effective at showing trends and comparisons.
Bottom Line

ChartBlocks has an excellent free plan, which is a big plus. The ease of use for creating basic charts and graphs is also outstanding.

Datawrapper was created specifically for adding charts and maps to news stories. The charts and maps created are interactive and made for embedding on news websites. Their data sources are limited, though, with the primary method being copying and pasting data into the tool.

Once data is imported, charts can be created with a single click. Their visualization types include column, line, and bar charts, election donuts, area charts, scatter plots, choropleth and symbol maps, and locator maps, among others. The finished visualizations are reminiscent of those seen on sites like the New York Times or Boston Globe. In fact, their charts are used by publications like Mother Jones, Fortune, and The Times.

The free plan is perfect for embedding graphics on smaller sites with limited traffic, but paid plans are on the expensive side, starting at $39/month.

Good data visualization: include multiple representations of data
Scatter plots can show a multitude of data, especially when color-coded to show more points.
Bottom Line

Datawrapper is an excellent choice for data visualizations for news sites. Despite the price tag, the features Datawrapper includes for news-specific visualization make it worth it.

D3.js is a JavaScript library for manipulating documents using data. D3.js requires at least some JS knowledge, though there are apps out there that allow non-programming users to utilize the library.

Those apps include NVD3, which offers reusable charts for D3.js; Plotly’s Chart Studio, which also allows designers to create WebGL and other charts; and Ember Charts, which also uses the Ember.js framework.Data visualization examples: voronoi maps
Voronoi maps are an interesting way to show geographic data.
Bottom Line

D3.js is only suitable for those designers who either have access to a programmer for help or have programming knowledge themselves.

Google Charts
Google Charts is a powerful, free data visualization tool that is specifically for creating interactive charts for embedding online. It works with dynamic data and the outputs are based purely on HTML5 and SVG, so they work in browsers without the use of additional plugins. Data sources include Google Spreadsheets, Google Fusion Tables, Salesforce, and other SQL databases.

There are a variety of chart types, including maps, scatter charts, column and bar charts, histograms, area charts, pie charts, treemaps, timelines, gauges, and many others. These charts can be customized completely, via simple CSS editing.

Beyond the tutorials and forum available, there’s limited support

Data visualization tools: Google Charts
Combo charts show trends and comparisons.

Data visualization methods: geocharts
GeoCharts are just one method of visualizing data with Google Charts.

Data visualization best practices: annotations
Annotations make charts and graphs easier to understand.
Bottom Line

Google Charts is a great option if a designer is somewhat comfortable with coding and wants a powerful, free solution. Being able to use any SQL database as a data source makes it a good option for large data sets, too.

FusionCharts is another JavaScript-based option for creating web and mobile dashboards. It includes over 150 chart types and 1,000 map types. It can integrate with popular JS frameworks (including React, jQuery, React, Ember, and Angular) as well as with server-side programming languages (including PHP, Java, Django, and Ruby on Rails).

FusionCharts gives ready-to-use code for all of the chart and map variations, making it easier to embed in websites even for those designers with limited programming knowledge. Because FusionCharts is aimed at creating dashboards rather than just straightforward data visualizations it’s one of the most expensive options included in this article. But it’s also one of the most powerful.


Huge number of chart and map format options
More features than most other visualization tools
Integrates with a number of different frameworks and programming languages

Expensive (starts at almost $500 for one developer license)
Overkill for simple visualizations outside of a dashboard environment

Source: https://www.toptal.com/designers/data-visualization/data-visualization-tools

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