As you embark on the Data School journey and create your first data visualization, you will undoubtedly ask yourself the following question: What is a data visualization, and why am I making it in the first place?
Although simple, this question does not find a unique and definite answer. Indeed, the data science literature is filled with competing definitions, and every book you open will offer a slightly different explanation of what data visualization really is. Some are straightforward and descriptive:
"Data visualization is a way of representing information and insights in a graphical format that enables communication, exploration, and discovery." - Stephen Few, author of "Information Dashboard Design: The Effective Visual Communication of Data."
some are more technical:
"Data visualization is the process of using graphical and non-graphical elements to represent complex and abstract information and data sets, where the goal is to communicate insights, patterns, and relationships within the data to a target audience through the selective use of visual encodings, perceptual cues, and multidimensional scaling techniques, informed by an understanding of the human visual system, statistical and mathematical principles, and principles of effective communication design." - Tamara Munzner, author of "Visualization Analysis and Design."
while others appeal to humor:
"Data visualization is like a magician taking boring numbers and turning them into a mesmerizing performance. The trick is to make the data disappear and leave only the insights." - Andy Kirk, author of "Data Visualization: A Handbook for Data Driven Design."
and others are more illustrative:
"Good data visualization is like a refrigerator for the mind; it keeps things cool and organized." - Alberto Cairo, author of "The Functional Art: An Introduction to Information Graphics and Visualization."
In fact, there are many definitions of the term data visualization because it is a multi-disciplinary field that encompasses various aspects such as design, statistics, information technology, and communication. Data visualization can have different interpretations and objectives depending on the context in which it is being used, such as business intelligence, scientific research, data journalism, or art. Furthermore, the people that create visualizations come from varied backgrounds and have different sensibilities that transpire in the way they define what they do. Additionally, the development of new technologies and techniques for representing and visualizing data continues to expand the possibilities and applications of data visualization, leading to new and diverse definitions.
Although finding a single definition of the term data visualization is proving difficult, it appears that its purpose suffers no debate. Indeed, in one way or another, experts agree that the prominent role of data visualization is to UNDERSTAND. Whether that be by uncovering hidden patterns in the data, discovering the unknown, finding answers, or improving questions, data visualizations should help you understand the data you have and help you draw better insights from it.