Of every 10 people on earth, one lives on an island.  That person has an excuse for not knowing about modern data visualization techniques.  For the rest of us, I would like to present: the Sunburst chart!

Before we start visualizing data, we need to understand data hierarchies.  We will take the simple example of Date.  We have a commonly shared agreement on the hierarchical structure for dates.  The first level of a date is the year; this is the largest volume of individual dates.  The second level would be month; there are still many dates in a month, but not as many as a year.  Finally, the day number is the lowest level representation of the date.  This is a simple representation of a data hierarchy.

Seldom does data standalone in a categorical hierarchy.  Departments rollup to divisions, cities rollup to territories, and products rollup to product groups.  Sometimes, moving or drilling up and down the hierarchy is acceptable, but what if we could give that hierarchical data a visual presence on the chart?

For simplicity purpose, we will use the product data set we used in the previous blog post.  Current visualizations would look something like the combination chart below.

This isn’t a horrible representation of data, but it is far from effective as we discussed in the previous post.  This chart asks the user to compare 4 various colors that are nominal, evaluate lengths that are similar, and determine slopes that are unnecessary.

We know from the previous post that a Treemap chart would be a better way to visualize this information. However, there is an additional visualization that helps us determine how the data makes up the whole product offering; the Sunburst.

Sunburst Chart

Sunburst charts measure values set to something that resembles a pie chart – visualizations of nominal, hierarchical datapoints and interval,.  Below is the same data from above, however, represented as a sunburst.

With the sunburst, we can see the largest product segment is Widgets based on the position (first in a counter-clockwise orientation).  We can also process the Product Names that make up the Product Group because they are the same color hue, however, use color saturation to define them as distinctly different.  The length of the segments helps us understand the segments portion of the whole offering. Finally, we can see how large sub segments are compared to the parent as well as the whole.

Modern visualizations allow authors to encode data points in ways that were previously never available.  Sunburst charts are a great way to represent the nominal, hierarchical data within a company’s data structure.

Surprisingly, too much data can skew our perception of reality within the data.  Identifying outliers and anomalies within the data points may be necessary to get a better picture of what’s occurring.  In the next post within this series, we will discuss a chart that attempts to bridge the gap between the descriptive analytics and predictive analytics that is called the Box Plot chart.