Data Visualization takes some practice before you get really good at it. It takes an understanding of the data in front of you and determining what you want to use of it. It takes understanding the software tools to make a graph. It takes utilizing design techniques to communicate messages in a graph about the data in understandable and attractive ways. It takes understanding your audience to recognize what will peak their interest as you craft a narrative out of your graph.
At its core, "data visualization" is "data communication" or "data storytelling." You use visuals to communicate and describe data. Data by itself lacks context, looks dense, and does not clearly show patterns. Data visualization is a method of reporting information, because it can bring data to everyone, quickly. And by the way, when we say "everyone," let's make it everyone--think about adding elements of inclusivity and accessibility in to your visualizations, too.
The value of a data visualization is that it should help people understand the underlying data. But a poorly designed visualization can be hard to figure out how to read it. Using good design techniques, you can more effectively process how you want to set up your visualization.