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. ChartBlocksĬhartBlocks claims that data can be imported from “anywhere” using their API, including from live feeds. The drag-and-drop editor makes it easy to create professional-looking designs without a lot of visual design skill. Infogram is a great option for non-designers as well as designers. Public version doesn’t allow you to keep data analyses private.Non-free versions are expensive ($70/month/user for the Tableau Creator software).Lots of video tutorials to walk you through how to use Tableau.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. 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. 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. 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. Output options include multiple chart formats as well as mapping capability. There are hundreds of data import options available, from CSV files to Google Ads and Analytics data to Salesforce data. Tableau has a variety of options available, including a desktop app, server and hosted online versions, and a free public option. Many are very basic and have a lot of overlapping features.īut 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. There are dozens, if not hundreds, of applications, tools, and scripts available to create visualizations of large data sets. This data visualization shows the Human Rights Protection index (from 1950 to 2014) and the Human Rights Violations index (in 2014) for 50 countries. 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. Those tools also have a place among the “best” tools out there.įinally, there are cost considerations. Some data visualization tools focus on a specific type of chart or map and do it very well. There are exceptions to the variety of output criteria, though. Most of the tools below can output both images and interactive graphs. The best tools also can output an array of different chart, graph, and map types. In fact, the very best can even handle multiple sets of data in a single visualization. The best tools can also handle huge sets of data. Others are lacking in those areas, eliminating them from any list of “best” tools, regardless of their other capabilities. Some have excellent documentation and tutorials and are designed in ways that feel intuitive to the user. There are some incredibly complicated apps available for visualizing data. The best data visualization tools on the market have a few things in common. What Do the Best Data Visualization Tools Have in Common? 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. 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. What Are Data Visualization Tools?ĭata visualization tools provide data visualization designers with an easier way to create visual representations of large data sets. 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. It’s not as if designers can simply take a data set with thousands of entries and create a visualization from scratch. That’s where data visualizations come in.Ĭreating data visualizations is rarely straightforward. Sometimes, data sets are so large that it’s downright impossible to discern anything useful from them. Consuming large sets of data isn’t always straightforward.
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