Speaker 1: You talked in your most recent pain point there about data visualization. You are an expert at data visualization. And do you have some best practices for our listeners?

Speaker 2: Yes. So I'm thinking through all my six different classes. All of my, I've been blogging a decade now. I'm about to have my, my 10 year anniversary is popping up on my calendar in a couple of days. I have 312, 315 blog posts. I have about a hundred YouTube videos now. So, um, here I, here I am running into one of my pain points, right? I'm like, how do you take all that data and actually just distill it. And if I had to pick some top data viz tips, it would be. To declutter your graph, dashboard, report, et cetera, diagram table, declutter first. We can talk about what that means. It basically means deleting half the extra ink that doesn't need to be there. Half the software default settings that are very outdated, that are very 1990s era graphic design, not based on the latest brain science of how we read graphs. Declutter first, highlight your key takeaway message in a dark color, use brand colors, make sure it's accessible for people who have color vision deficiencies. Of course, there's nuances to color and then put your takeaway message in the title. There's nuances to fonts and texts that are skimmable and easy to read and at the appropriate reading level. But it's, it's basically just that you declutter. You've used some dark colors. You use some takeaway text. That's about it. That's about all I teach in like different ways, said different ways for different audiences. There's report specific advice, presentation, specific advice, dashboard, specific applications of that. But that's really the key to good data viz and good data storytelling.

Speaker 1: Crystal clear. Declutter the graph. Try to remove half of the ink. That makes perfect sense to me. It is interesting how the defaults in pretty much any plotting package are, I guess, trying to show off in a way, like all of the different things that the plot could do. Um, but yeah, most of it is irrelevant. Uh, and yeah, simplifying is that is something that I, that I think I'm pretty good at getting right. The dark colors. Uh, so that, so that was number one was declutter. Number two is dark colors that are legible, uh, including to colorblind people. So you can be thoughtful about the, uh, color palette that you select so that it's legible to the widest number of people. Um, and then number three is have the takeaway messages in the title. So that's similar to what you said with the whole data storytelling premise. So that was at the report level. So at the report level, instead of having a topical title, you've got a takeaway title, but then similarly on each of the charts, you've got a takeaway message right there in the title. Yep.

Speaker 2: And, you know, there are little nuances to titles like, this is a big culture change for a lot of groups, especially if there's a lot of master's level and PhD people who are used to just very technical writing and maybe they have to write peer reviewed articles or go to very scientific conferences as part of their job. And then, so for some people listening, I might be asking you to make a major culture shift in your organization, but it's okay to take baby steps. So how I take baby steps with some of the, the agencies I work with, as I say, keep your topical title that you're used to keep the topic like sales, whichever title you would come up with earlier, you know, just a regular old title of the topic, but right underneath below there, we can call it a subtitle, just put the takeaway message, you know, like, like that, that's a win. I consider that a win. Another nuance to titles, for example, would be you can add annotations, which are just text boxes. That's it. That's just in the body of the chart. It's especially helpful for line charts. If something happened, some, something contextual happened, some milestone happened and the graph, all of a sudden you see the numbers going up or down because some external thing happened. The person making the graph usually knows what that thing is that happened. You, the funding doubled, you hired a new staff person, you changed your approach, a policy change. It's so painfully obvious to the person making the graph, why some sharp increase or decrease might have happened, but it's not painfully obvious to the audience who sees that graph among 50 million other graphs every single week. So you just, at the simplest level, you just add a text box on the body of your graph and you say, like, in March, 2020, this thing happened, like, just make it really obvious what's going on on the graph.

Speaker 1: That's a perfect example of something that I seldom do and seems so obvious now that you've said it. This, the title of this episode is going to have to be, everyone must listen to this episode. It's going to be, uh, all of the data presentation mistakes that I've made in the past, I'm going to have to do it again. I'm going to have to make the same mistakes you've been making, but didn't even know you were, uh, yeah, that's okay, that's okay now people know, uh, so adding annotations, I guess that's something that you can do even in a tool like Excel.

Speaker 2: Yeah. I mean, you can add data labels. I hate to just use line chart examples. What's another example? Chart type, if it's a donut chart or a bar chart or a tree map or a, whatever diagram you can add it within the data label. I actually, oh, did I publish this yet? Did I know it's going to, it's going to come out early 2023. I have a blog post on how to do that. I took gif recordings. We had a hurricane last week in Florida, so I had no internet, but my laptop was working and I just cranked out all the how-to blog posts that have been on my, my rainy day list. For like years. So anyway, I have a blog was coming out on like how to actually do that. It's very simple. You can add a text box, like don't get hung up too much on the software. How to's I, I like everyday software, but you can do this in all the software programs. It's just the idea of putting a call out box on the graph again. So it's not buried inside a paragraph or it's not just us, you know, assuming that the audience knows that they might not know that obvious thing.