Predictive Intelligence Usage Analytics dashboard

The Predictive Intelligence Usage Analytics dashboard is a central location to understand the effectiveness and overall value of all your Predictive Intelligence solutions. View metrics for model training successes and failures. Monitor prediction statistics including breakdowns by individual model.

For your models in the Classification, Similarity, and Clustering capabilities, the Predictive Intelligence Usage Analytics dashboard gives you visibility into training and predictions. You can specify the time periods to report on, as well as select specific solutions for a deep dive.

With the ml_report_user or ml_admin role, view the Predictive Intelligence Usage Analytics dashboard by navigating to Predictive Intelligence > Dashboards > Monitoring.

The dashboard has separate tabs for each capability. The Classification tab opens by default, or you can select Similarity or Clustering. Each tab contains a set of reports in the form of widgets.

You can drill down into the underlying records by selecting a report's chart or graph, which opens a query-filtered list. Many reports in the Training Statistics section of PI Usage Dashboard are drawn from the ml_solution table. Reports in the Prediction Statistics section are drawn from the ml_predictor_results table.

Date Range

The Date Range selector opens a calendar picker where you can select the time frame for the reports. Your selected date range applies to all widgets on the current tab.

The calendar picker offers a variety of preset dates under its Standard subhead. Choose from Last 3 months, Today, YTD (year to date, from January 1 of the current calendar year), and so forth.

You can also choose Custom range to select your own dates. Enter dates directly into the Start date and End date fields, or select a date range using the calendar. Then select Apply to update the reports in all widgets on the page.

Available metrics for Classification and Similarity

The following tables describe the widgets available on both the Classification and Similarity tabs, unless otherwise noted. The Clustering capability has different widgets, so refer to the Available metrics for Clustering section on this page.

Tableau 1. Widgets available in Training Statistics for Classification and Similarity solutions

Widget	Description
Total Solutions	Total number of Classification (or Similarity) solutions created.
Total Active Solutions	Total number of Classification (or Similarity) solutions that are active.
Total Successful Model Trainings	The number of Classification (or Similarity) jobs that have been successfully completed in the instance.
Total Failed Model Trainings	The number of Classification (or Similarity) jobs that have failed in the instance.
Trained Solutions - By Month	Total trained Classification (or Similarity) solutions aggregated monthly.
Active Solutions - By Month	Total active Classification (or Similarity) solutions aggregated monthly.
Classification (or Similarity) Training Status	The distribution of Classification (or Similarity) model training states.
Active Status Distribution	The distribution of active versus inactive records. The "true" portion indicates active items, while "false" represents inactive ones.
Training Frequency Distribution	The training frequency distribution across all Classification (or Similarity) solutions. The available options range from Run once up to Every 180 days.
Update Frequency Distribution (Similarity only)	The update frequency distribution across all similarity solutions. The available options range from Run once up to Every 180 days.

Tableau 2. Prediction Statistics

Widget	Description
Total Successful Predictions - By Month	Count of total Classification (or Similarity) predictions calculated per month.
Total Successful Predictions	Total number of successful predictions made on all Classification (or Similarity) solutions.
Total Failed predictions	Total number of failed predictions made on all Classification (or Similarity) solutions.

For the following widgets, use the selector labeled Classification solution or Similarity solution to choose an individual model.

Tableau 3. Selected Active Classification Solution Details

Widget	Description
Successful Predictions per Solution	The number of successful predictions for the selected Classification (or Similarity) solution.
Failed Predictions per Solution	The number of failed predictions for the selected Classification (or Similarity) solution.

Available metrics for Clustering

The following table describes metrics available on the Clustering tab of the Predictive Intelligence Usage Analytics dashboard.

Tableau 4. Training statistics for Clustering

Widget	Description
Total Solutions	The total number of clustering solutions created in the instance.
Total Active Solutions	The number of active clustering solutions in the instance.
Total Successful Model Trainings	The number of clustering jobs that have been successfully completed in the instance.
Total Failed Model Trainings	The number of clustering jobs that have failed in the instance.
Trained Solutions - By Month	The number of clustering trainings triggered per month.
Active Solutions - By Month	The number of active clustering solutions trained per month.
Clustering Training Status	A pie chart showing the training status distribution across all clustering solutions in the instance.
Active Status Distribution	A pie chart showing the distribution of active and inactive clustering solutions.
Training Frequency Distribution	The percentage of training frequencies set across the clustering solutions.
Update Frequency Distribution	The percentage of update frequencies set across the clustering solutions.

For the following widgets, use the selector labeled Clustering solution on the Clustering tab to pick an individual model.

Tableau 5. Selected Cluster Solution Breakdown

Widget	Description
Cluster details	The details of each cluster created in the specified solution.
Number of clusters	The number of clusters created in the specified clustering solution.
Total Records Clustered	The total number of records clustered in the specified clustering solution.
Number of updates completed (in last 7 days)	The number of update jobs completed for a specified clustering solution.
Details of Last Update (in last 7 days)	When the clustering solution was last updated, number of new clusters created, records assigned to existing clusters, and new clusters in the last update.