A chart is a way of communicating a finding, and a bad one can hide the finding or even mislead people. Data visualization principles are the habits that make a chart easy to read and honest: the right chart for the question, nothing unnecessary on the page, and colour used with purpose.
You'll start with choosing the right chart for your data and your message, whether that is a comparison, a trend, a part-to-whole, or a relationship. Then you'll learn to declutter a chart, use colour to guide the viewer's eye, and spot the tricks that make a chart misleading, such as truncated axes and cherry-picked ranges.
These principles apply in every tool. In the next module, Power BI & Tableau, you'll put them to work building real dashboards.
How to choose the right type of chart for the data you have and the message you want to get across.
How to strip a chart down to what matters: removing gridlines, borders and other clutter so the message stands out.
How to use colour to direct attention, highlight the key data, and keep everything else in the background.
How charts can mislead through truncated axes, distorted scales, and selective data, and how to avoid these mistakes in your own work.