Here’s When to Use Data Visualization Tools, and Why They’re Helpful

It doesn’t matter whether you subscribe to a “right brain” or “left brain” camp – the human mind is drawn to aesthetically pleasing shapes, colors, and patterns. And that’s 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 to understand information that may not be easy to scan and work with in its raw form .

Data visualization tools—such as Tableau or Google Charts—allow users to import small or large amounts of data and automatically turn raw data into beautifully designed scenes or graphics. This not only makes it easier to process information internally but can also provide a simple way to pitch data-driven principles 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 of data visualization tools in the workplace and how using the said tools can help to quickly and efficiently capture vast amounts of information.

What are data visualization tools?

Data visualization and information visualization tools were designed to make it easy and efficient for designers to work and talk with large data sets at the surface level. This may sound like a clear representation of small data sets, but can also represent up to hundreds or even 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 visualizations – which not only simplifies a designer’s job, but also helps to ensure that all data visualizations are free from human error and data entry mistakes. will be free Data visualization tools help designers interact with large data sets in order to easily draw conclusions or interpret usable information in a way that would not be possible with hard data sets alone.

While many data visualization and information visualization tools can come with a steep learning curve, most designers agree that investing the time spent learning these powerful tools not only makes it easier to reach conclusions or understandable information, but also ensures more efficient workflow. With less chance of human error.

Which 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-understand to more complex tools that can take some time to learn and work with in 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 many different output options – e.g. that maps and charts or graphs.

Depending on the type of data you work with and how committed you are to learning and using the tools available, there are a few different data visualization tools and scripts that are tailored to your field and specific day-to-day. Will stand out on base – need of the day.

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

Of course, there are many other data visualization tools that may better suit more drilled-down needs. Popular data visualization tools across the board include Infogram, Google Charts, DataWrapper, Grafana, and Fusion Charts.

Why use a data visualization tool?

There are three key elements that data visualization tools help to cover when working with large data sets or complex information. Successful data visualization tools will help you understand your audience, create a clear framework for interpreting the data and drawing conclusions, and tell a visual story that could not be as clean and concise with raw data points.

Data visualization tools—when used properly—will help to better tell a given story and better pull off information, spot trending patterns, and draw conclusions from large data sets. Data visualization tools also lean into more aesthetically pleasing approaches to mapping and tracking data. It goes beyond simply sticking information on a pie chart and instead uses design information, color theory, and other practices to present the information in an interesting yet easy to understand way.

Although data visualization tools have always been popular in the design space, the right data visualization tools can assist with any task or area of ​​personal interest. For example, data visualization tools can help journalists and editors track trending news stories to better understand readers’ interest. These tools can be used for anyone who wants to track individual interest data points to better understand a bigger picture, such as tracking specific changes in weather in one’s neighborhood or community.

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