"What is the point?" This is a question that comes up often in my workshops when we are looking at graphs and discussing how they can be improved. In this post, I discuss the importance of making your main takeaway clear and apply this idea to a specific example.

This graph is ok. It gets the job done. But it could be so much better. If you've taken the time to do a robust analysis, why not take the time to make your data visualizations reflect that? In this post I look at a before-and-after, discussing changes that can take a graph from good to great.

In this post, I discuss the challenge of the dual y-axis and my rework of a #MakeoverMonday challenge.

In this post, I feature an example before-and-after from a recent workshop and discuss the importance of connecting the dots for your audience.

When visualizing survey data, it's always seemed to me like showing where you're at is only part of the picture. There is important context that comes with where you could be.  In this post, I explore this idea in the context of a specific example.

In this post, I makeover less-than-ideal visuals from a recent USA Today graphic summarizing diversity stats across a number of Bay Area tech companies and discuss my design thought process when doing so.

This is a case where the story being told wasn't quite right, or at least wasn't exactly the story I would tell after looking at the data in a couple of different ways. Here, I'll walk you through my thought process and makeover.

This visual breaks pretty much every best practice out there when it comes to effective graph design. Check out this post, where I comment on the design choices and demonstrate what this data has the potential to be.

Slopegraphs can be useful to show comparisons between groups. For example, when reporting employee survey results, a slopegraph can be used to show a given team's feedback across survey categories compared to the overall company. Check out this post to see an example and read more about slopegraphs.