Training Data Studio
Last updated
Last updated
The Training Data Studio enables users to create applications and define rules efficiently. By leveraging system discovery data, defining precise window rules, and using filtering options, you can streamline data collection and application tracking effectively.
This studio offers the following key features:
Create Applications from System Discovery: When System Discovery is enabled, applications based on the collected discovery data can be generated.
Create Window Rules: If an application is in Training Mode, new window rules can be defined for that application.
Follow these steps to navigate to Training Data Studio:
Go to Admin Panel → Configure Data Collection.
Select an application:
Choose System Discovery to generate application rules.
Select a specific application to generate window rules.
In the Data Collection Granularity section, click Go To Training Data Studio to access the training studio.
The Training Data List appears at the bottom of the Training Data Studio and displays a list of all unique process names, URLs, and title combinations collected for the selected application. The Total Visits column shows how frequently each combination appears, helping you assess data volume.
This list helps you configure applications/windows based on detected patterns in process names, URLs, and titles.
Follow these steps to create a new application rule:
Review the Training Data List to identify patterns.
Enter the application or window name.
Define the rule by entering values in the Process Name, URL, and Title fields.
Click Preview matched training data for the rule. A popup will display all matching rows from the training data.
Verify that the information is correct. If no data appears, adjust the rule.
Click Create Rule to create the rule.
The matched rows will be removed from the listing, leaving only unmatched data for further processing.
Training data can be grouped and customized using advanced filtering options to streamline processing.
You can choose which columns (Process Name, URL, and Title) to display, and the data will be grouped based only on the selected columns.
For example, if the same URL is accessed using different browsers, enabling Process Name and URL columns will display the following data:
msedge.exe
3
chrome.exe
2
If only the URL column is selected, the data will be combined into a single row:
5
Follow these best practices when selecting columns for filtering training data.
If your URLs or titles contain variable IDs, you can remove them to improve grouping. For example, if you have a URL grouping as follows:
sap.com/invoice/123/pay
5
sap.com/invoice/456/pay
3
sap.com/invoice/789/pay
2
Set the Remove IDs from URLs after keyword field to the value invoice/
to ignore the variable ID and get the following results:
sap.com/invoice/XXX/pay
10