First, we have to think about what it is that we want our audience to be able to do with the data (function) and then create a visualization (form) that will most efficiently and most accurately convey the data’s meaning.
When you display the data visually using the right chart, you’ll be able to easily uncover meaningful patterns and correlations from a set of otherwise indecipherable numbers.
Below are the four data relationships that are used when visualizing the data:
- A comparison tries to set one set of variables apart from another and display how those two variables interact, like the number of visitors to five competing websites in a single month.
- A composition tries to collect different types of information that make up a whole and display them together, like the search terms that those visitors used to land on your site, or how many of them came from links, search engines, or direct traffic.
- A distribution tries to lay out a collection of related or unrelated information simply to see how it correlates, if at all, and to understand if there’s any interaction between the variables, like the number of bugs reported during each month of a beta.
- A relationship tries to show a connection or correlation between two or more variables through the data presented, like the market cap of a given stock over time versus the overall market trend.