Here’s when to use data visualization tools, and why they’re helpful

It doesn’t matter whether you subscribe to the “right brain” or “left brain” camp—the human mind is drawn to aesthetically pleasing shapes, colors, and patterns. And that’s exactly where data visualization tools come into play. Data and information visualization tools were designed to make data points easier to digest, to help draw conclusions, and discern information that might not be as easy to scan and work with in its raw form.

Data visualization tools—like Tableau or Google Charts—allow users to import small or large amounts of data and automatically transform the raw data into beautifully designed visuals or graphics. This doesn’t just make it easier to process information internally but can also offer a simplified way to pitch data-driven theories or display KPIs in meetings and presentations.

So what exactly are data visualization tools and what do they bring to the table? Read on to better understand the role data visualization tools can play in the workplace and how using said tools can help make processing large amounts of information quick and efficient.

What are data visualization tools?

Data visualization and information visualization tools were designed to make it easy and efficient for designers to work with and talk about large data sets on a surface level. This can look like a clear representation of smaller data sets but can also represent all the way up to hundreds or millions of data points in a quick and easily scannable format.

The role of modern data visualization tools is to help automate the process of creating a visualization—which doesn’t just make a designer’s job easier but also helps ensure that all data visualization will be free of human error and data entry mistakes. Data visualization tools help designers interact with larger data sets in order to easily draw conclusions or discern usable information in a way that would not be feasible with hard data sets alone.

Although many data visualization and information visualization tools can come with a steep learning curve, most designers agree that investing the time it takes to learn these powerful tools doesn’t just make coming to conclusions or discerning information easier but also ensures a much more efficient workflow with less chance of human error.

What are the best data visualization tools?

There are dozens of data and information visualization tools on the market right now that range from basic and easy-to-grasp to more complex tools that can take a while to learn and work into your day-to-day workflow.

The best data visualization tools should be easy to use (or come with a comprehensive tutorial), handle large amounts of data points, and be able to convert different data subsets into multiple different output options—such as maps and charts or graphs.

Depending on the type of data you tend to work with and how much you expect to commit to learning and using the tools available, there are a few different data visualization tools and scripts that will stand out based on your field and specific day-to-day needs.

One of the most popular data visualization tools among web designers—and anyone who wants to quantify data points—is Tableau, which offers free or paid options that make importing data easy, with hundreds of data import options available. There’s also an extensive option of color-coded graphs and aesthetically pleasing charts that not only work for discerning conclusions from data points in-house but can also be used to convey information in high-level presentations and pitches.

Of course, there are plenty of other data visualization tools that might better suit more drilled-down needs. Popular data visualization tools across the board include Infogram, Google Charts, Datawrapper, Grafana, and FusionCharts.

Why use data visualization tools?

There are three major elements that data visualization tools help cover when working with large data sets or complicated information. Successful data visualization tools will help you understand your audience, set up a clear framework to interpret data and draw conclusions, and tell a visual story that might not come off as clean and concise with raw data points.

Data visualization tools—when used properly—will help to better tell a given story and make it possible to better pull information, see trending patterns, and draw conclusions from large data sets. Data visualization tools also lean into a more aesthetically pleasing approach to mapping and tracking data. It goes beyond simply pasting information onto a pie chart and instead uses design know-how, color theory, and other practices to ensure information is presented in an interesting but easy-to-understand manner.

Although data visualization tools have always been popular in the design space, the right data visualization tools can aid just about any field of work or personal interest. For example, data visualization tools can help journalists and editors track trending news stories to better understand reader interest. These tools can also be used for anyone looking to track personal interest data points to better understand a larger picture, such as tracking the specific changes in weather in one’s neighborhood or community.