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.

There is a recommendation I find myself often voicing to workshop participants: Think about what you want your audience to be able to easily compare. Put those things as physically close together as you can and align them along a common baseline. This post features a makeover applying this recommendation.

I've posted a number of times about Pew Research articles. Well, not the articles exactly, but rather the visuals they contain. To be honest, it's rare that I read the actual article. I scan the headlines as they hit my inbox and if something piques my interest, I follow the link and scroll through the article, not reading, but taking a discerning look at the graphs. Check out this post for makeovers of two Pew Research graphs on the topic of women bosses.

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.

My disdain for pie charts is well documented. While opinions on their usefulness run the gamut, I am certainly not alone in my contempt. In my workshops, I sometimes get the question, "In what situation would you recommend a pie chart?" For me, the answer is never. There are a number of alternatives, each with their own benefits. It's these alternatives that I'll focus on in this post.

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.