Visualization methods and best practices

- I read a post lately about how the person designed this beautiful dashboard and no one was using it. This left the data professional perplexed and frustrated. I get that. But it immediately made me start thinking of why. Why, if it is so great, are the users not using it? Well, have you ever heard of beauty is in the eye of the beholder? It could be as simple as the data analyst designed something that only the data analyst can use. Looks great, but no one else understands it. It could be that the data analyst just loaded this beautiful dashboard, sent a link, and said, "Here's your great, new dashboard." Best practice number one. For a moment, be the person you're designing for. If you want to see what this feels like, imagine driving a 10 or 15 year old vehicle and then go sit in the newest car on the lot with the most features. The dashboard will likely take you more than a minute to translate before you drive it. Now, imagine that someone hands you the keys and says, "Take it for a spin. It's amazing." What do you do? Depending on you, you freeze, go with it, or get out? In the same scenario, imagine that that car salesman came out and explained the differences between your car dashboard and this new dashboard, or at least hit the high points with you. What would you do then if they directed you where to look to make you feel more comfortable for going for a drive? Always take time to document and provide a little bit of training on your visuals. Be consistent. Use the same color for the same item all the way through. If my brain says, "This product is blue on this stacked bar," then every time I see a reference to this product, it will be blue. And then when I believe this new visual has the same blue, is the same item, and I realize it's a totally different product, I get stuck on why isn't this the same? And the data is not showing me anything. Don't overcomplicate to show your fancy vis skills. I do understand that people want to use advanced visuals to show their skills. But the point of the dashboard has nothing to do with your skills, but providing information. If you provide valuable insight through correct visuals and layout, they will believe you to be a visual magician, and they will not care that you presented it in simplified visuals. Be sure to title, label, and add tooltips appropriately. People should be able to read a title for context, be able to easily read the labels, and hover over to get additional insight, not just see the same thing the visual already shows. Remember that a picture is worth a thousand words. And if we could all make decisions by consuming thousands of lines of data, we wouldn't need visuals. Not all data visualization is a chart or graph. Make appropriate use of cards for high level totals and other aggregate functions. And remember, a table, matrix or pivot is also a visual presentation of data, and some people prefer that matrix to a chart. So it never hurts to give them both to meet the needs of the audience. Always remember that your visuals will be used to provide information. So make sure that it does it in a way that people can quickly understand and make decisions.