You can use Data Query to report on the specific data of the Collections features. Typical use cases include:
- Reporting on data updates to meet internal audit or compliance requirements
- Monitoring and notifying data changes
- Triaging or troubleshooting feature configuration and usage
To learn how to use Data Query, see Data Query. If you need further assistance, you can join the Data Query forum in Zuora Community.
Data Query tables for the Collections features
The following Data Query tables contain information about the Collections features:
- Table for Advanced Payment Manager
Collections_ApmPaymentRuns- Each row represents a payment run initiated in Advanced Payment Manager.
- Table for Collections Window
Collections_CollectionsWindowInfo- Each row represents an account that is in collections based on the system condition and the conditions you defined.
- Tables for Configurable Lockbox
Collections_ConnectorExecutions- Each row represents a processing record of the configured lockbox file format.
Collections_LockboxRecords- Each row represents a file record of the configured lockbox file format.
Collections_Lockboxes- Each row represents a lockbox file format configured in Configurable Lockbox.
Collections_LockboxPayment- Each row represents a payment record that has been completed or is in progress.
- Tables for Configurable Payment Retry
Collections_RetryAttempts- Each row represents a payment retry attempt initiated in Configurable Payment Retry.
Collections_CustomerGroups- Each row represents a customer group configured in Configurable Payment Retry.
Collections_MetricSnapshots- Each row represents a record of the retry metics.
Collections_RetryCycles- Each row represents a retry cycle.
- Tables for Notes
Collections_Groups- Each row represents a user group in Notes.
Collections_Note- Each row represents a note.
Collections_Replies- Each row represents a reply.
Collections_Commentables- Each row represents a user in Notes.
You can use
SHOW COLUMNS to list the columns that are available in each Data Query table. For more information, see Constructing SQL Queries in Data Query.