Choosing the Right Chart for Your Data
Selecting the appropriate chart for a dataset can be challenging, but narrowing down your options is easier when you consider the number of data points and whether the data is continuous or discrete.
Number of Data Points
One Data Point
- Charts: Pie, point, and gauge charts.
- Use Cases: These charts aggregate a single data point and display it as a number or part of a whole. Useful for showing metrics like a risk score or the status of assessments.
Two Data Points
- Charts: Bar, column, and line charts.
- Use Cases: These charts use two data points to populate horizontal and vertical axes. Ideal for modeling data such as risk scores by category or compliance ratings per regulation.
- Special Use of Pie Charts: Pie charts can measure one data point against a category by using the series attribute to split data. For example, they can show average or maximum risk scores split by a category.
Three Data Points
- Chart: Bubble chart.
- Use Cases: Bubble charts include a horizontal axis, a vertical axis, and a size variable to create a scatter plot with an additional layer of information.
- Example: Plot impact vs. likelihood of risk, with bubble size representing the cost of implementing controls. Points in the top-right corner with smaller bubbles represent quick fixes, while larger bubbles may indicate more significant investments.
Additional Series Field
- Bar, column, line, and bubble charts also support a series field to split data by another category. For more information on these settings, refer to the relevant documentation.
Continuous vs. Discrete Data
Discrete Data
- Definition: Categorical variables with distinct values (e.g., risk category, scores 1–5, or defined ranges such as 0–5, 6–10).
- Best Charts: Bar and column charts are ideal for discrete data.
Continuous Data
- Definition: Variables with infinite possible values (e.g., date/time or monetary values).
- Best Charts: Line charts are optimal for continuous data, as they provide a smooth representation over a range.
Chart Selection Summary
| Chart Type | Data Points | Use Case |
|---|---|---|
| Point Chart | One | Displays a single number, such as the count of critical risks or average scores. |
| Pie Chart | One (+ series) | Visualizes proportions, such as the number of assessments in each status. |
| Gauge Chart | One | Displays a single value in the context of a target, such as an average risk rating. |
| Bar/Column | Two (+ series) | Models discrete data, such as risk scores by category or by third party. |
| Line Chart | Two (+ series) | Best for continuous data, such as tracking risk scores over time. |
| Bubble Chart | Three (+ series) | Visualizes relationships among three variables, such as impact, likelihood, and cost. |
| Risk Matrix | Two | Plots risks on a matrix using impact and likelihood values. Ideal for visualizing risk distribution. |
Choosing a Trendline
Trendlines help predict values by showing relationships between variables. They are supported in bar, column, and line charts.
| Trendline Type | Description |
|---|---|
| Linear | A straight line for simple, linear datasets. |
| Exponential | A curved line for datasets where values rise or fall at increasing rates. |
| Logarithmic | A curved line for datasets showing rapid change before leveling out. |
| Polynomial | A curved line for fluctuating datasets. |