Benefits, Purpose, and Importance of Data Visualization

Network visualizations show the relationships and connections between multiple datasets. Examples include matrix charts, word clouds, and node-link diagrams. Data visualization helps us to understand what certain data is telling us, presenting it in a way that’s accessible to a range of audiences—not just data experts. It’s how you bridge the gap between your expertise as a data analyst or data scientist, and those people who can use or act upon the insights you discover. Data visualization is the graphical or visual representation of data.

Sign up for a free trial of ThoughtSpot and see how easy it is to get started. Static data visualization is the most basic form of data visualization. It involves taking data and creating a static image, such as a graph or chart, that represents that data.

Books about data visualization

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They say a picture is worth a thousand words, and this is especially true for data analytics. Data visualization is all about presenting data in a visual format, using charts, graphs, and maps to tell a meaningful story. It’s a crucial step in the data analysis process—and a technique (or art form!) that all areas of business can benefit from. Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics, and even animations.

There is such a huge variety of visualization tools available to designers that it can be hard to decide which one to use. Data visualization designers should keep in mind things like ease of use and whether a tool has the features they need. The outputs are dynamic, responsive maps in a variety of styles, from image overlays to symbol maps to density maps. It uses SVG to create the images, so designers can use CSS to customize the visuals of their maps.

The map showed that the worst-affected households were all drawing water from the same well, which eventually led to the insight that wells contaminated by sewage had caused the outbreak. The sample visualizations in the next section were created using R, which is kind of a swiss army knife of data visualization. Here, we’ve introduced just a handful of data visualization types. If you want to learn more, check out our complete guide to different types of data visualization and when to use them. In this section, we’ll introduce some useful types of data visualization. We’ll also point you to our more comprehensive guide where you can learn about additional data visualization methods and how to use them.

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It can help you to quickly identify key areas of performance or areas that you need to improve. The value of data visualization that it enables people to perceive, engage with, and understand data more easily. The right visualization can bring everyone to the same level of understanding, regardless of their level of expertise. Visualizing big data in real-time is now more of a must-have than a nice-to-have for modern companies. Customer demands and the overall business landscape move fast, and real-time data visualization is how you can stay up to date and ahead of the curve. One of the most significant benefits of data visualization is how it enables the easier absorption of large amounts of business data.

The scatter plot is the standard way of showing the relationship between two variables. Bullet charts are another specialist chart for comparing a true value to one or more benchmarks. A funnel chart is a specialist chart for showing how quantities move through a process, like tracking how many visitors get from being shown an ad to eventually making a purchase. Violin plots and box plots are used to compare data distributions between groups. Similarly, a stacked area chart modifies the line chart by using shading under the line to divide the total into sub-group values.

Categories of Data Visualization

Exploratory, which seeks to visualize data in a manner that’s conducive to further exploration and hypothesis testing. Business users breathe easy; exploratory visualizations aren’t subject to statistical methods that are as strict. Because they work more as frameworks in which to explore, rather than as explanations of specific business problems. Another task that shows up in data exploration is understanding the relationship between data features. The chart types below can be used to plot two or more variables against one another to observe trends and patterns between them.

There has been progress in developing a theory of graphics, especially thanks to Wilkinson’s Grammar of Graphics and Hadley Wickham’s implementation of it in the R package ggplot2 . There is continuing work and better understanding of the problems of color and perception. Graphics that were rarely used and difficult to draw, such as parallel coordinate plots (e.g., Theus, 2015) and mosaicplots (e.g., Unwin, 2015), have been refined and developed.

Additionally, it provides an excellent way for employees or business owners to present data to non-technical audiences without confusion. Data visualization charts offer a way to organize or visualize a collection of data points. The term “chart” can refer to many visual types, including graphs, maps, infographics, and diagrams; data visualization tables can even be considered charts. Keep reading to learn about more specific types of data visualizations below. Explanatory data visualizations help you tell this story, and it’s up to you to determine which visualizations will help you to do so most effectively.

But suppose you don’t have an idea about why performance is lagging—you don’t know what you’re looking for. You want to mine your workbook to see what patterns, trends, and anomalies emerge. What will you see, for example, when you measure sales performance in relation to the size of the region a salesperson manages?

Does Your Company Actually Need Data Visualization?

Essentially, we need data analytics in order to make smart decisions—and data visualization is a crucial part of that. In this guide, we’ll tell you everything you need to know about data visualization . We’ll explain what data visualization is, why it matters, and how you can do it effectively. We’ll also explore some of the most common types of data visualization, as well as the tools you can use to create them.

• Drill down, zoom out, separate the wheat from the chaff, and get insights you didn’t know you were looking for.
• The outputs are dynamic, responsive maps in a variety of styles, from image overlays to symbol maps to density maps.
• Usually there is a reason why we are interested that dataset that we are looking at.
• These graphs show the distribution of numerical data using an automated data visualization formula to display a range of values that can be easily interpreted.
• All businesses must incorporate data visualization tools and reap transformative benefits in their critical areas of operations.

Essentially, you visualize your data any time you want to summarize and highlight key findings and share them with others. With that in mind, let’s consider what kinds of insights you can convey with data visualizations. From a business perspective, it enables companies to learn from the past and plan ahead for the future. In fields like healthcare, it can help to improve patient care and treatment. In finance and insurance, it can help to assess risk and combat fraudulent activity.

Bar charts encode value by the heights of bars from a baseline. That’s not to say that declarative charts shouldn’t generate discussion. But the discussion should be about the idea in the chart, not the chart itself. By answering just two questions, you can set yourself up to succeed. Design visual brand experiences for your business whether you are a seasoned designer or a total novice. You can save your time as well as brainpower by using customizable infographic and chart templates.

Google Charts

In the world of data science, data visualization is much more than a word. It’s a whole process that provides solutions to a lot of problems we’re facing today. Whether it’s big data that we need to analyze or a presentation we need to make for the stakeholders, data visualization always plays a vital role. SAS technology helps you prepare data, create reports and graphs, discover new insights and share those visualizations with others via the Web, PDFs or mobile devices.

Data storytelling

Like any data analytics project, it’s important to define a clear purpose for your data visualizations. What are the priorities in terms of what you want to convey and communicate? Data visualization truly is an art form—but the goal is always, first and foremost, to provide valuable information and insights. If you can do this by way of beautiful visualizations, you’re onto a winner. So, when creating data visualizations, it’s important to adhere to certain best practices. These will help you strike the right balance, keeping your audience engaged and informed.

What Is Data Visualization and Why Is It Important in 2022?

For example, when viewing a visualization with many different datapoints, it’s easy to make an inaccurate assumption. Or sometimes the visualization is just designed wrong so that it’s biased or confusing. In our increasingly data-driven world, it’s more important than ever to have accessible ways to view and understand data. After all, the demand for data skills in employees is steadily increasing each year. Employees and business owners at every level need to have an understanding of data and of its impact.

Explanatory data analysis provides context for and helps explain the insights identified through exploratory efforts. For example, it may help explain why customers aren’t buying a new product you recently launched. Now that you know why data visualization is important, let’s explore a few different types of commonly used visuals. The final chapter of this guide discusses aspects to consider before selecting a data visualization tool for your organization. A dot map created by English physician John Snow in 1854 to understand the cholera outbreak in London that year. The map used bar graphs on city blocks to indicate cholera deaths at each household in a London neighborhood.

It’s important that you use a data visualization that accurately reflects the situation, so that your stakeholders can make well-informed decisions. When presenting marketing data, either to colleauges, your boss or a client, data visualization also plays an important role. Better and more clear visualizations will help you to tell your story in an impactful way. Basically, data visualizations are the lifeblood of savvy marketers. Last but not least, using three-dimensional data visualization to build interactive models, maps, games, virtual events, etc., might be the next big thing in the way we use big data. Simply put, data storytelling provides actionable insights in a more meaningful way, facilitating better decision-making.

Big data visualization often goes beyond the typical techniques used in normal visualization, such as pie charts, histograms and corporate graphs. It instead uses more complex representations, such as heat maps and fever charts. Big data visualization requires powerful computer systems to collect raw data, process it and turn it into graphical representations that humans can use to quickly draw insights. See our list of great data visualization blogs full of examples, inspiration, and educational resources.

Combining data with the right visual formats lets you present information in a far more digestible way. Machine learning automates the creation of analytical models and enables predictive analytics. It’s frequently confused, though not correctly, what is big data visualization with artificial intelligence. Learn why SAS is the world’s most trusted analytics platform, and why analysts, customers and industry experts love SAS. Data Visualization9 min read How to Use Sankey Diagram to Visualize Sales Pipeline Report?

Despite the price tag, the features Datawrapper includes for news-specific visualization make it worth it. 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 https://globalcloudteam.com/ the primary method being copying and pasting data into the tool. 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.