Data visualization is an umbrella term for visualizing all types of data through charts, graphs, and maps. The ultimate goal is to visually represent your data in an accessible and easy-to ...

In my visualization post, What Makes a Good Data Visualization I mentioned two aspects of data to consider. You want a graph that conveys ideas from the data that are too complex to explain ...

Learn the five biggest downfalls of data visualization. Visuals can tell a story and explain complex ideas, but they must be used effectively. Learn the five biggest ... prioritizing design and ...

We’ve all heard that Big Data is the future. But according to Phil Simon’s new book The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions, that may not be ...

Data visualization allows viewers to see the patterns in reams of numbers. It’s the craft of simplifying the complex. Done poorly, it confuses, misleads, or even lies.

As explained in this Edraw article, every data visual has one of the five key objectives—distribution, composition, relationship, trend and comparison. • Distribution: The visuals show how ...

To experience the breadth of Excel’s data visualization offerings, let’s take a tour of some of the most useful charts, starting with the basic ones and moving to the more advanced. To follow along, ...

The two graphs below show the exact same data, but use different scales for the y-axis: On the left, we’ve constrained the y-axis to range from 3.140% to 3.154%. Doing so makes it look like ...

Graph Visualization Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data Compound graphs, a frequently encountered type of data set, have a hierarchical tree structure ...

Data visualization takes your data (numbers) and places it in a visual context, such as a chart, graph, or map. It also helps create data stories that communicate insights with clarity.