If you are a One Model user, you have been exposed to Metrics. Metrics are quantitative measurements. The number of employees hired and the number currently employed at your company are both metrics.
While this article does not cover creating Dimensions, it's worth mentioning them here to avoid confusing the two. Dimensions are attributes of your data. Work location of employees is a dimension. When viewing data in One Model, you will almost always be viewing metrics that are grouped or filtered by dimensions.
To access the metrics creation screen, navigate to Explore and select Create / Edit in the header area of the current list of metrics. This will open the screen for creating a new metric from scratch. To edit or copy an existing metric, select the pencil icon next to the existing metric in the left menu while on the Create / Edit screen. It's almost always better to copy an existing metric since it gives you a good starting point. The risk of doing so however is that you unintentionally modify the metric you're copying rather than copying it. If you modify an existing metric and save it, there is no way to undo it. You will have to try to remember how it was configured before the update.
Use caution not to unintentionally modify an existing metric!
The menu section of the screen contains basic "File menu" options, in the following order:
Cancel changes (does not undo once the metric is saved)
The pencil icon next to the existing metrics opens that metric for editing.
The configuration of the metrics is performed in the Settings section.
The first five settings control the more administrative aspects of the metric. This includes what it's named, where it can be found, and who has access to it.
Name (required) - You can name your metric whatever you want but it's best to be consistent in your naming conventions
Description - Information about how the metric is calculated. This is visible when selecting metrics from a dashboard/storyboard.
Category (required) - This is where the metric will live in the list of available metrics in explore. A category is required when creating a metric.
Subcategory - This is the second level of where the metric will live in the list of available metrics in explore. Although a category is required when creating a metric, a subcategory is not required.
Metric Permissions (required) - Here you select the roles that should have access to this metric. At a minimum, select your own role and the Admin role.
The settings from this point onward define how the metric is calculated.
Metric Definition (required) - A metric definition can be as simple as referencing a particular column and can also get quite complex. Both Base Metrics and Calculated Metrics can be created. A base metric is derived from columns in the data model whereas a calculated metric is a metric built off of other metrics. Arithmetic calculations and, static numbers are available to be used for all Metrics. The DATEDIFF function is also available to be used for metrics based on tables where the dates are in the same table.
For a base metric, select a column from a table in the Tables section of the list of entities on the left. An example of a base metric is Hires.
A calculated metric is created by adding an existing metric or metrics from the Metrics section on the left list. An example of a calculated metric is Termination Rate, which is Terminations / Average Headcount.
Arithmetic calculations, static numbers, and the DATEDIFF function can be utilized in either type of metric.
Measure Format / Precision / Decimals (required) - It's up to you what you select here, although if your metric is a count or sum of whole numbers, you won't need decimals.
Aggregate Context (required) - This section only becomes visible once you create a Metric Definition based on a Fact Table. This section will not show for calculated or derived metrics. Knowing whether you're creating a cumulative, average, or point in time metric is important to consider when selecting your aggregate context. To better understand the different types, you may want to consider reading this help doc: Difference between Cumulative, Average and Point in Time Input Measures
Aggregate Type - If your metric is being created from a non-numeric column, the only options here will be Count and DistinctCount. You might use DistinctCount to calculate the number of Job Applications on which there was activity during the selected time period. Since there can be more than one row per application, DistinctCount of Application ID prevents each one from being counted more than once. If in your metric definition, the value generated is numeric, you have significantly more options. Sum and Average are the most commonly used.
Period Filter - If None is selected here, it will use the time context you select in your queries in explore at face value. For event based metrics such as Hires or Terminations, None is the correct choice since you want to see how many happened throughout the selected time period. StartOfPeriod and EndOfPeriod are used for point in time metrics, such as Headcount.
Filters - Selecting Edit dimension filters in the Filters section will switch the items displayed in the left menu from Metrics and Tables to Dimensions. Choose the dimension(s) you wish to filter by and the values you would like to include. There is currently not the ability to exclude values.
Time Functions - Time Functions work in combination with Time Models in explore to create robust methods of exploring data across time. While more often than not you'll be leaving None selected here, understanding how time functions work is useful. Rather than explain these somewhat complex functions here, we have created a separate help document at the link above that explains them in some detail.