SAS Visual Analytics Display Rules: Gauge – Level

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This is the fourth and final post in a series about the available Display Rules in SAS Visual Analytics.

Report - Level
Table – Level
Graph – Level
Gauge – Level (this article!)

Recall from the previous articles, that there are three types of display rules. Here are examples for each type.

Color-mapped Value: based on a Category data item.
Expression: based on a measure data item expression.
Gauge: based on a measure data item interval definition.

The conditions are defined in the Rules pane. These Boolean expressions are evaluated for each visualization based on the assigned data Roles.

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SAS Documentation: Working with Display Rules.

Gauge – Level

In this article, I will be focusing on the Gauge - Level Display Rules that apply to the Gauge Objects. We saw in the Table – Level Display Rule article that the List Table Object supports a gauge display rule however, it only supports a subset of gauges.

The recommendations in this article will span more than just the display rule since the dedicated gauge object itself has several aspects to consider when using in your report.

The Gauge Object, has six Shape options and six Style options which includes a Customizable Style which gives over thirty-six possible combinations.

Despite the many ways you can style a Gauge Object, the fundamental steps to define the Gauge – Level Display Rule are the same. I like to think of the steps as an equation.

Add the Gauge object from the Object pane to the report page.
Assign Data Roles.
A default interval expression Display Rule will be defined based on the Data Roles. Customize as necessary.
Success – you have your gauge.

Now let’s dive into the different options, combinations, and customizations for the Gauge Object and Gauge – Level Display Rules.

Gauge Object

To satisfy the curious, I put together a sample of the available Shape and Style gauge combinations. I kept the default three equal interval expression Display Rule and the default red, yellow, green coloring so that you can easily see how the same Display Rule definition looks across the different gauge combinations.

Gauge Objects became popular with the rise of the dashboard style of reporting in the 1990’s when business needs required a quick way to assess their key performance indicators (KPIs). These gauge objects are similar to what you would see on a dashboard for a plane, automobile, or manufacturing machines for monitoring fuel, pressure, temperature, etc.

At a quick glance, which style and shape do you prefer? I tend to prefer the thermometer styles since it only shows the interval color that has been met and displays the interval ranges.

Data Roles

Now that we have examples of the types of gauges we can include in our report, let’s look at the data role assignments and best practice recommendations.

Notice in the Roles pane that there is only one required data role and that is for the Measure assignment. This tells us that the gauge will aggregate the measure data item for the data source and apply any filters defined.

The Target Role is a measure field and it should match the scale of the Measure Role as the measure represents the magnitude of how close it is to the target. Another optional Role is the Group role. This will act as the by group and the Measure (and Target if assigned) will be aggregated by the category data item assigned to the Group Role.

One best practice recommendation to consider, if you are using the Group assignment or using multiple gauges on your report, is the scale. The scale is essentially the range of numbers that help to measure or quantify the target. If you are in a business where your Group values have consistent targets or performance, then you are lucky and this may not apply to you. Otherwise, consider using a percentage-based measure scale so that even if the magnitude of the scale is different, you can easily compare these values.

In this first example, if you have Unit Yield (actual) and Unit Yield (target) values, you could use the Unit Yield (rate) = Unit Yield (actual) / Unit Yield (target). This is especially helpful, in this case, when the Product Lines have widely different unit yield actuals and targets.

In this second example, using a percentage-based Measure allows you to easily duplicate the gauge and change the Group Role as you explore your data.

In this third example, I used a cumulative percent of total across the months to show the progress to the Year’s Order Total. I can now easily use the Year drop-down prompt to explore the data without having to adjust the scale.

Gauge – Level Display Rule Now we need to explore our third operand in our equation, the Display Rule. When you use a percentage-based Measure Role assignment there is no requirement to have the Target Role, and the intervals can be defined between 0 and 1.

Notice that in the Display Rule overflow menu there is an option to Recalculate.... This brings up a dialogue window that helps you to easily define equal intervals between lower and upper bounds. The default lower and upper bounds are prepopulated with values which are queried from the data source based on the Role assignments.

You can then manually change any of the interval bounds as you like. You can also use the color chip to select the desired color you want associated with each interval.

In the case where you are using actual values, and not percentages, and using both a Measure and Target Role assignments then you may run into the informational warning that The gauge contains an out of bounds target which is not shown. This is because the default lower and upper bounds for the interval display rule is queried from the Measure data item. You can use the Recalculate window to make the adjustments to either the lower or upper bound as needed.

Notice that the intervals have to be manually entered and cannot yet be dynamically driven. This is why it is recommended to, if your data allows, use a percentage-based measure and interval definition.

Another recommendation is to be sure the lower bound for any bar-based gauge starts at zero. This is the industry wide recommendation for any bar chart or bar gauge to start at zero. The other styles, such as the arc or dial variations, can have a lower bound not start at zero but use caution as most real-world applications of these gauges have conditioned us to use zero as a starting point.

Summary

Here are the key points for using the Gauge – Level Display Rules which encompasses more than just the display rule itself since it uses its own Gauge Object.

Use a percentage-based measure so that it can easily adjust for additional data and across different by groups. This allows for an easy Gauge – Level Display Rule interval definition to be between 0 and 1.
For any bar style gauge objects, be sure to start the lower bound at zero. Also, consider using zero as the lower bound, unless your measure includes negative values, as we have been condition by real-world applications to assume the starting point is zero.

This now concludes the series for using Display Rules in SAS Visual Analytics.

Report - Level
Table – Level
Graph – Level
Gauge – Level (this article!)

Here is a list of the supplemental enablement materials I mentioned in this article as well as other helpful resources:

Get to know the List Table
Creating Hierarchies to use in SAS Visual Analytics Reports
SAS Visual Analytics Cell Graphs to enhance List Tables and Crosstabs: Article | YouTube
SAS VA Report Example: Add a scope to an aggregated measure: Article | YouTube
Use Report Themes to quickly change your data color palette
SAS VA: Use Custom Categories to create user-defined categories for dates, measures, or categories: Article | YouTube
SAS VA: Automatic Actions Part 1 – Easy exploration for multiple data sources: Article | YouTube
SAS Visual Analytics 8.1: Configuring prompts with different source data: Article | YouTube
Tips for working with multiple data sources in SAS Visual Analytics: Article | YouTube
SAS Visual Analytics Report Examples using Container Objects: Article | YouTube

Find more articles from SAS Global Enablement and Learning here.