Create Dataset Metrics

In a dataset, you can define one or more metrics to perform calculations with one or more rows of data. Metrics enable you to create:

• Calculations based on a defined aggregation

• Calculations to pivot rows to columns

Metrics definitions are stored as a SQL expression in a SQL statement for the dataset, but defined metrics are not available for use in the SQL Lab.

To create a metric:

1. In the Edit Dataset window for a dataset, click Metrics.

2. In the Metrics tab area, click Add Item.

3. Type information for the following fields:

• Metric: The name of the metric

• Label: The metric's label — this is the value that the user sees as the metric's name. Specify a unique label that clearly represents the metric information.

• SQL Expression: The SQL expression that calculates the metric. This is the statement that computes the value of the metric, and it is also a tooltip when the user hovers over the question mark "?" icon.

4. To edit other fields associated with the metric, select the expansion arrow on the left side of the metric row.

5. For each metric, you can specify the following optional details in the expanded fields:

• Label: A user-visible label for the metric's name (same editable field in collapsed metric row).

• Description: A short description of the metric — this appears as a tooltip when the user hovers over the letter "i" icon.

• D3 Format: Specify the D3-style number format to use for number fields. For example:

  • Given a value of 1234.567

    • .2% = 123456.7%

    • .2k = 1K

    • ,.2r = 1,200

• Certified By: You can specify a value for the person or team who certified the metric for use.

• Certification Details: Any descriptive text about the certification details.

• Warning: A warning message that, if defined, appears in the Metric selection field. Warnings can be helpful to note situations like when a metric has SQL runtime performance implications, or might be in a “beta” mode and to be used only in test charts or dashboards.

6. Click Save.