We know that visualization is the best and most practical way to tell the story of data. However, many individuals, especially those who haven’t had classical design training, often lack the foundational knowledge needed to be successful to effectively present visual data. As such, it’s important to take the next step and begin to understand what specific visual techniques and best practices will provide the best insights or elicit the reaction that you intend with your data.
"If you do a quick Google search for ‘data visualization,’ or if you simply browse the catalog of options in most BI tools, you'll find that there's no shortage of visual options available to you. But you should ask yourself, ‘Is this simply an option, or is this an optimal, efficient, and effective option?’ What generally happens when we become more intentional with a craft is we learn that there are basics that can be heavily leaned on to put us in a great position for success. It’s no different when it comes to data visualization." — Corey Campbell, Director of Design, RevUnit
Knowing your options and choosing the right one for your business and company goals will yield greater results and have a further-reaching impact.
When you know more about the ways in which certain visuals impact perception, you will have greater comprehension of how graphs, tables, and other display formats affect data visualization, so it’s important to understand the basics of these different formats and the options that are available to you.
In the Complete Guide to Better Data Visualization, we break down the analysis types further to help you determine which graph types to use. Here is a snapshot of what graph types will be covered in the guide:
Time series trends and comparisons display quantitative values along multiple, sequential points in time.
Best graph types to use: lines, lines and points, points only, vertical bars, vertical boxes
Ranking displays how distinct/separate quantitative values relate to one another sequentially by magnitude, from low to high or high to low.
Best graph types to use: points only, bars
Part-to-Whole relates the individual parts of a grouping to the whole of that grouping magnitude, from low to high or high to low.
Best graph types to use: bars, stacked bars
Deviation displays the degree to which one or more sets of quantitative values differ in relation to a primary set of values.
Best graph types to use: bars, lines
Distribution displays the way in which one or more sets of quantitative values are distributed across their full range from the lowest to the highest and everything in between.
Best graph types to use: bars, lines, points, boxes
Correlation displays the relationship between two paired sets of quantitative values to demonstrate whether or not they are related, and if so, the direction of the relationship and the strength of the relationship.
Best graph types to use: points, bars
Geospatial features the geographical location of values, positioning those values on a map.
Best graph types to use: color intensity, lines, points (varying size and/or varying color intensity)
Nominal comparison displays a series of discrete quantitative values to highlight their relative sizes.
Best graph types to use: bars, points
A good rule of thumb is to stay away from pie charts and default to bar graphs. And in our opinion, a highly underrated format is the bullet graph. It was developed by Stephen Few (a pioneer in data viz) and is used to showcase a primary measure against other measures in a single view.
Bottom line: By knowing what display formats are best tailored for your data visualization aims, you’re far more likely to gain critical insights into your data sets.
Ready to get started? Check out our Complete Guide to Better Data Visualization and download our “3 Tips for Better Data Storytelling with Your BI Tools” cheat sheet.