A Practical Guide to Data Visualization: Definition, Examples and Learning Resources
Data visualization refers to the graphical representation of information and data. Using visual elements like charts and maps, a data visualization makes it possible to see and understand unusual trends or values in the data in a very accessible way.
|A Practical Guide to Data Visualization|
In the world of big data, data visualization tools and technologies are essential for analyzing huge volumes of information and making decisions based on data.
Benefits of effective data visualization
Our eyes are naturally drawn to the colors and repetitive patterns. We can quickly distinguish red from blue or a square from a circle. Our culture is essentially visual, marked in particular by art, advertising and cinema.
Data visualization is an art form that captures our attention and draws our eyes to the communicated message. By observing a chart, we can quickly identify unusual trends and values. The fact of seeing allows us to integrate information quickly. Data visualization is storytelling with a specific purpose. If you’ve ever watched a spreadsheet filled with data and couldn’t spot a trend, you understand that a visualization is much more effective.
In the age of Big Data
The era of Big Data is shifting into high gear. Visualization is playing an increasingly important role in helping us make sense of the billions of rows of data generated every day. Data visualization helps tell stories by presenting data in an easy-to-understand way and highlighting unusual trends and values. Effective visualization tells a story by removing irrelevant data to present only that which is relevant to the subject.
However, it is not just a question of presenting a nice graphic or an infographic full of additional information. For visualization to be effective, you need to find the right balance between content and form. The simplest graphic can go completely unnoticed or, on the contrary, send a powerful message. Likewise, the most compelling visualization may speak for itself or miss its purpose altogether. The data and visual elements used must go hand in hand: knowing how to combine relevant analysis and powerful storytelling requires special skills.
The importance of data visualization in all businesses
It would be difficult to find a sector of activity that would have no interest in better interpreting its data. In scientific and technical fields, in administration, in finance, in marketing, in the service sector or in sport, data visualization is playing an increasingly important role.
We could go on and on about data visualizations (we’re on the Tableau site after all), but it’s important to talk about real-world applications. Faced with the generalization of visualizations, skills in this area are increasingly useful in the world of work. The better you can get your message across visually, whether it’s in a dashboard or a presentation, the better you’ll be able to leverage that information.
The concept of an ordinary data scientist is gaining ground and everyone’s skills are evolving to meet new market needs. It is increasingly important for professionals to know how to use data to make decisions and use visuals to tell your discoveries. Although traditional training clearly distinguishes between creative storytelling and technical analysis, the professional world is now looking for talent capable of excelling in these two areas, both associated with data visualization.
Data visualization in action
To fully understand data visualization, you obviously have to see it in action.
With the proliferation of visualization galleries and data sources, it’s hard to know where to start. We have selected 10 remarkable examples of data visualizations across the centuries, including historical campaign maps as well as analyzes of film scripts or causes of death.
The Tableau Public Gallery contains many visualizations designed with our free Tableau Public tool. Our Dashboard Starters are templates you can use to design your own professional dashboards, and Today’s View highlights the best creations from members of our community. There are also many blogs and books on data visualization, offering examples, explanations and information on best practices.
The different types of visualizations
When you talk about data visualization, the first image that comes to mind is probably of graphs or pie charts. While these types of charts are recurring items, each visualization has its own unique set of information. The most common graphics are not necessarily the most suitable for your needs. There are many visualization methods that can be used to present data in an effective and attractive way.
Most common types of visualizations:
Examples of more specific visualizations:
You can combine all of these charts in a single dashboard.
Learn more about data visualizations and learn how to design them
If you are feeling inspired or would like to learn more, there are many useful resources to consult. Many data
visualization and data journalism enthusiasts are happy to share their tips or recommendations.
Getting started: blogging about data visualizations
Check out our list of blogs full of examples that you can use as an inspiration or a teaching resource.
The authors of these blogs are often experts, have published books on the subject, or teach the theory behind data visualization. In their blog, they analyze recent visualizations or the latest trends in the industry. Many of them also offer reviews or tutorials to help you design effective visualizations.
Some of these blogs also bring together visualizations from around the world and highlight the most exceptional. Blogs are a good way to learn more about specific aspects of data visualization or to find inspiration by discovering exceptional projects.
For theoretical knowledge: historical examples and works
Discover our list of books on theoretical and practical approaches to data visualizations.
If blogs are useful for following all the developments in a sector as dynamic as that of visualizations, the books help you to acquire theoretical knowledge. Throughout history, humanity has always sought to present data in a visual form. One of the first books on data visualization, first published in 1983, laid the foundation for a booming industry today.
The more recent books still allow to approach the theory and the techniques of visualization, while offering tips and timeless examples. Some books are even entire visual projects published as a manual.
Free and paid training
There are many free and paid data visualization training and resources, including here on the Tableau site. We offer videos, articles and white papers, aimed at both complete beginners and Data Rockstars. At this time, we will not be suggesting third-party training in this article.
Note on data visualization tools and solutions
There are many tools for analyzing and visualizing data, some very simple and intuitive, and others more complex and obscure. Of course, some tools are more suitable than others if you want to learn visualization techniques, and not all of them can adapt to the specific needs of a sector or company. If you want to learn more about the different solutions available, read this article or check out independent reviews such as the Gartner Magic Quadrant.
Remember that it is more important to acquire good theoretical knowledge and skills than to have specific tools and solutions. As you learn these skills and focus on best practices, you will be able to explore and develop your own style to create visualizations and dashboards that are like you. Data visualization is an area that is not going to go away. It is therefore important to build a solid foundation in terms of analysis, storytelling and data exploration, on which to rely whatever tools are used.