Kurt Buhler points something out:
Effective visualizations provide context so that you can interpret the numbers and what they mean to you. Is this number bad or is it good? This is particularly important for visuals that aim to provide a quick, 3-second overview, like cards, KPIs, and simple trendlines. You can provide context by comparing to a target, but if no target is available, you can also compare to a measure of central tendency, like the average or median. However, instead of comparing to an aggregate, you might also want to compare to other categories.
Consider the following example, which shows the desired end result for this article: a plot which highlights a selected value so that the user can compare it to all others. This example uses some DAX and formatting with a line chart and scatterplot to achieve the result of a joint plot atop a jitter plot. If you want to learn more about what a joint plot or a jitter plot is, we gave an overview of these and similar chart types in a previous article.
This is something I find frustratingly difficult with Power BI. Kurt does a great job of showing how to get there, but it seems like it should be a lot easier to do.