How many items (data points) will you display for each variable? Only a few or many?.How many variables do you want to show in a single chart? One, two, three, many?.To determine which chart is best suited for each of those presentation types, first you must answer a few questions: Unless you are a statistician or a data-analyst, you are most likely using only the two, most commonly used types of data analysis: Comparison or Composition. There are four basic presentation types that you can use to present your data: In this article, I’ll try to undo some of the damage by sharing some of the best practices for data visualization and representation and, hopefully, save some kittens in the process. To avoid common pitfalls in your presentations, it wouldn’t hurt to review the basics of data visualization. But it is also a copout to blame PowerPoint - it is just software, not a method. It should have come with a warning label and a good set of design instructions back in the ’90s. There is no question that PowerPoint has been at least a part of the problem because it has affected a generation. But it’s not.Ĭountless innovations fail because their champions use PowerPoint the way Microsoft wants them to, instead of the right way. PowerPoint could be the most powerful tool on your computer. Unfortunately, it is far from anything related to good, and I stand before you as guilty myself.Īnd if you think I'm too cynical about this, don't take only my word for it. Many of us come from the "PowerPoint generation" - this is where the roots of our understanding of data visualization and presentation lie.
To turn your numbers into knowledge, your job is not only to separate noise from the data, but also to present it the right way. There is a load of data in the sea of noise. Making sense of facts, numbers, and measurements is a form of art – the art of data visualization.
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