Overview of data visualization types
When you create a data visualization, you select the type of visualization to display. Each visualization type is suited to show different data.
Score visualizations
This type of data visualization shows a single value or score as a number or percentage. Scores are often used to show how a particular value or metric compares to a target or benchmark. They can be useful for tracking progress or identifying areas for improvement, for example showing a company's or division's overall performance.
| Visualization | Description |
|---|---|
| Single score visualization Image omitted: inline-data-vis-single-score.png Single-score visualizations display a single aggregate value that is important to your business.Single score data visualization example</td><td> | |
| Dial visualization Image omitted: inline-data-vis-dial.png Dial visualizations show where a single value lies across a range from minimum to maximum expected values. Visually, a "needle" points to the value, and the dial is colored in for values up to the needle.Dial visualization example</td><td> | |
| Gauge visualization Image omitted: inline-data-vis-gauge.png Like dials, gauges show where a single value lies across a range from minimum to maximum expected values. In addition to dial functionality, you can set colored data ranges to help users understand what the value represents.Gauge visualization example</td><td> |
Time series visualizations
Time Series visualizations show data over time. All time series visualization types share configuration options. They differ in use case, depending on whether you want to emphasize data trends or the differences between individual data points. For more information about these use cases, see Create time series data visualizations.
Note: In addition to data from within your instances and imported data sources, you can also use MetricBase data in time series visualizations. For more information, see MetricBase application.
| Visualization | Description and use case |
|---|---|
| Visualizing trends in a data source | |
| Line Image omitted: inline-data-vis-line.png line visualization | Shows how one or more values change over time by connecting a series of data points with straight lines. Use a line visualization to emphasize the trend in the data. Consider line visualizations to be the default choice for showing a time series. If you’re unsure of which visualization to use, use a line. |
| Spline Image omitted: inline-data-vis-spline.png spline visualization | Shows how one or more values change over time by connecting a series of data points with a fitted curve. The curve emphasizes the trend over individual data points. Spline visualizations let you take a limited set of known data points and approximate intervening values. |
| Scatter Image omitted: inline-data-vis-trend.png scatter visualization - med | Shows unconnected points for values in the Y-axis against time in the X-axis. Usually the trend line is also shown. Use with a spread of data that can’t be usefully connected with a line. |
| Comparing scores in a data source | |
| Column Image omitted: inline-data-vis-bar-column.png column visualization | Shows changes in data over time by showing values as proportional vertical columns. Use either to visualize changes in one data source or to compare data sources. To compare data sources with a column visualization, either add data sources to the visualization, or place several column visualizations next to each other in a dashboard. |
| Step Image omitted: inline-data-vis-stepline.png Emphasizes changes in a data source between discreet points in time. Use to show small incremental changes, especially when a line visualization smudges the data.</td><td> | |
| Comparing scores or trends between data sources | |
| Area Image omitted: inline-data-vis-area.png Resembles a line visualization, but the area between the axis and line is emphasized with colors. Use with multiple data sources to highlight the relative contribution that each data source makes to the whole.</td><td> | |
Bar visualizations
Bar visualizations enable you to compare scores across data dimensions. Horizontal and vertical bar visualization types are available. They share all configuration options. In general, use horizontal bars for nominal or categorical data. Use vertical bars for ordinal or sequential data. Use different colors or patterns to distinguish different groups or categories. For more information, see Create a horizontal or vertical bar data visualization.
| Visualization | Description |
|---|---|
| Horizontal bar visualization Image omitted: inline-data-vis-bar-horizontal.png Bar visualizations show categories labeled on one axis and values on the other. Use vertical bars to compare ordinal data, especially when there aren’t too many categories, such as sales numbers grouped into buckets. Use horizontal bar charts with nominal data, such as incident severity or assignment group.- Horizontal bar visualization example - Vertical bar visualization example Pareto bar visualizations help you identify the most important dimension in a large set of dimensions. Columns show data in descending order. A line shows cumulative percentage. Pareto visualizations contain both bar and line graphs. The bars display the data in descending order from left to right, and the line graph shows the cumulative totals from each category in the same order. The left Y axis is the record count, and the right Y axis is the cumulative percentage of the total number of records evaluated.</td><td rowspan="3"> | |
| Vertical bar visualization Image omitted: inline-data-vis-bar-vertical.png Data visualization vertical bar type- med | |
| Pareto bar visualization Image omitted: inline-data-vis-pareto.png Data visualization pareto bar type |
Pie and Donut visualizations
Pie and donut visualizations show the relationship between parts and the whole of a data set. The segments of these visualizations should total to 100%. For more information, see Create a pie or donut data visualization.
| Visualization | Description | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Pie visualizations Image omitted: inline-data-vis-pie.png Pie visualizations are best when comparing 5–7 segments that total 100%, when no two segments have a value within 10% of each other. Donut visualizations are best for comparing no more than five segments that total 100%, when no two segments have a value within 10% of each other. The center of the donut can be used to show additional information. Semi-donut visualizations are best for comparing no more than four segments that total 100%, when no two segments have a value within 10% of each other. - Pie visualization example - Donut visualization example</td><td rowspan="3"> | |||||||||||||||||||
| Donut visualizations Image omitted: inline-data-vis-donut.png Semi-donut visualizations </td></tr><tr><td> Image omitted: inline-data-vis-semi-donut.png </td></tr></tbody> Multidimensional chartsMultidimensional visualizations enable you to show multiple variables in a single chart, and it can be useful for showing the relationships between different variables. They are useful when you have a lot of data, and you want to find patterns or trends that might not be immediately obvious. They're also good to use when you want to show the relationship between three or more variables.
Other visualizationsData visualizations can also show calendars, simple lists, indicator scorecards, and location.
Parent Topic:Creating data visualizations |