TL;DR: Effective data viz is centered on critical thinking, understanding the nature of your data / data story, your goals, and who you're communicating with. Not just about snazzy tools.
I can't count the number of times I'm asked "What tool should we use?" or "What should we make?" before answering "What story do we want to tell? And to whom?" With the democratization of data visualization through online tools, everyone benefits from knowing at least a bit about dataviz.
At the same time, we must take a step back and remember that the point of visualization isn't to make something pretty (though often visualizations do look lovely) but rather to communicate an idea.
As the author points out:
Managers who want to get better at making charts often start by learning rules. When should I use a bar chart? How many colors are too many? Where should the key go? Do I have to start my y-axis at zero? Visual grammar is important and useful—but knowing it doesn’t guarantee that you’ll make good charts. To start with chart-making rules is to forgo strategy for execution; it’s to pack for a trip without knowing where you’re going.
I also love that he gets into the distinctions between data visualization and designing frameworks / graphics / illustrations to visualize an idea and where to use what.
Give the piece a read and see what resonates with you. The author proposes some simple questions you can ask to guide your design process (for example, are you explaining/declaring or helping to explore the data?) that should drive your design choices far more than what tool you want to use.