In keeping with my prior post, I'm sharing another "most-photographed slide" from my recent workshops.
My voiceover typically sounds something like this: When it comes to storytelling with data, one very important component of stories is words. There are some words that absolutely have to be there: every graph needs a title and every axis needs a title. This is true no matter how clear you think it is from context. The only exception that comes to mind is if your x-axis is January, February, March, etc., you probably don't need to title it "months of the year." You probably should make it clear what year it is. Any other axis needs a title. Label directly so your audience doesn't question what they are looking at.
Don't assume that two different people looking at the same data visualization will walk away with the same conclusion. Which means, if there is a conclusion you want your audience to reach, you should state it in words. Use what we know about preattentive attributes to make those words stand out: make them big, leverage color and/or bold, and put them in high priority places on the page like the top.
Speaking of which, that title bar - stories have words: annotate with text - is precious real estate. It is the first thing your audience encounters when they see your screen or your page, so make it count. Use this space for active titles, not descriptive titles. If there is a key takeaway for your audience, put it there so they don't miss it. It will also help set up the content that is to follow on the rest of the page.
When you are communicating with data, there are some words that usually need to be there: data source, as of date, and perhaps notes on assumptions or your methodology. These are necessary words but they don't need to cry out for attention. Use what we know about preattentive attributes to emphasize the important parts of your visual and also to de-emphasize less critical pieces. Footnotes can be small, the text can be grey, and they can be in lower priority places on the page like the bottom.
Use words to title, label, and explain; they help make your data visualizations accessible!
To see this and other storytelling with data lessons firsthand, attend one of my upcoming public workshops.