Intro to Data Visualization What IS Data Visualization?

Merriam-Webster Dictionary defines data as

1. factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation
2. information in digital form that can be transmitted or processed
3. information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful

While the foundation of what we'll be discussing in this guide very much pertains to the first definition - factual information that can and should be used as a foundation for sharing information and making decisions - it's important to remember that data really is a collection of bits of information. This can take many forms, such as qualitative and quantitative data. These bits of information can also be used not only to inform, but also to persuade and affect change, for better or worse.

For the purpose of this guide, we're going to talk about how to use data to craft effective storytelling devices like tables and graphs to convey meaning greater than the sum of the individual bits of information you began with. We hope that you'll wield that power ethically!

According to Tableau, a visual analytics platform, 

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. Additionally, it provides an excellent way for employees or business owners to present data to non-technical audiences without confusion.

That doesn't sound so scary, right? Even if we didn't pay them any attention, we have all seen bar charts, line plots, and maps of various parts of the world. All of those visuals are ways that people have tried to communicate with you about the data they think is important or supports a point they're trying to make.

Why think about data visualization? It's all about communication. Especially in fields that often speak in numbers, like chemistry and engineering, we really need ways of explaining our interesting and important thoughts and findings to the rest of the world that aren't highly trained in our area of expertise. Thus, we need to think about how to use our data to communicate clearly to a general audience - in other words, how that audience can visualize our data in a way that tells them something meaningful.