MicroStrategy ONE

Conditional metrics as inputs for predictive metrics

You must create a filter and then a metric using that filter for each element of the attribute you use to group the metric. Repeat the process outlined below for each element.

Before you begin

This topic assumes you know how to create filters and metrics. For detailed instructions on those processes, see Steps to create a filter and Creating metrics in reports.

To create conditional metrics to use as inputs for predictive metrics

  1. In MicroStrategy Developer, open the Filter Editor. (How?)

  2. In the Object Browser, double-click the attribute on which to filter. The Attribute Qualification dialog box opens.

  3. Click Add and select an element.

  4. Save the filter and close the Filter Editor. You are returned to MicroStrategy Developer.

    For more information, see Steps to create an attribute qualification.

  5. Open the metric that needs filtering. (How?)

  6. In the Object Browser, double-click the filter created above. The Condition in the metric definition changes to reflect the filter.

  7. Click Level (Dimensionality). The Level (Dimensionality) component window displays below the Metric Definition area.

  8. In the Object Browser, double-click each attribute used in your data mart report. The attributes are placed in the metric expression.

  9. If the predictive metric is to be used to forecast values for elements that do not exist in your project, you must define the join type for the metric used as an input for the predictive metric to be an outer join. For example, the predictive metric is planned to forecast values for one year in the future. Since this future year is not represented in the project, you must define the join type for the metric used as an input for the predictive metric to be an outer join so that values are returned.

    To set the join type to outer to include all data in the dataset:

    • From the Tools menu, select Advanced Settings, and then Formula Join Type. The Metric Formula Join Type dialog box opens.

    • Select Outer and click OK.

  10. If you plan to export predictive metric results to a third-party tool, you should define the column alias for the metric used as an input for the predictive metric. This ensures that the name of the metric used as an input for the predictive metric can be viewed when viewing the exported results in the third-party tool.

    To create a metric column alias to ensure the column name matches the metric's name:

    • From the Tools menu, select Advanced Settings, and then Metric Column Options. The Metric Column Alias Options dialog box opens.

    • In the Column Name field, enter the name of the metric. This must be a valid column name for your database. For example, usually spaces and special characters cannot be included).

    • Click OK.

  11. From the File menu, select Save As. The Save As dialog box opens.

  12. Save the new metric.

    It is best when the column name matches the metric name so that the predictive metric can be automatically created when you import the predictive model. If the names do not match an existing metric when the predictive model is imported into MicroStrategy, the user will be prompted to manually identify the proper metric to use.

  13. You can now include the metric in a training metric to create a predictive metric, as described in Training Metric Wizard.