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Data 360: BYOL Data Stream Behaviour

Дата публикации: Apr 10, 2026
Описание

This article explains how BYOL data streams function in Salesforce Data 360.

Решение

Record Modified Field Removed in Create Stream Flow for BYOL Data Streams:

The "Record Modified" field has been intentionally removed from the Create Data Stream page in Data 360. This change was made to prevent confusion, as the field was often incorrectly used for incremental data loads. It has since been renamed to "Incremental Column" to better reflect its purpose.

If you don't see the "Record Modified" field when creating a BYOL Data Stream, no action is needed — you can proceed with creating your data stream as usual.

 

Understanding the Discrepancy in Stream Record Counts When Enabling or Disabling Acceleration:

If the record count of a BYOL (Bring Your Own Lake) stream differs between the query editor and the stream details page, this is expected behavior.

The last processed records count on the Data Stream details page reflects the last time the ingestion job ran with acceleration enabled. For BYOL streams, ingestion is user-controlled — acceleration can be enabled or disabled at any time.

If acceleration was previously enabled and has since been turned off, the total processed records will reflect only the data ingested into Data 360 (formerly Data Cloud) during the period acceleration was active. Once acceleration is disabled, this count no longer represents the total number of rows in the Data Lake Object (DLO).

How Incremental Ingestion Works:

  • The Incremental Column should represent a field that can track data changes over time.
  • During each run, the system identifies the maximum value of the selected incremental column from the previously ingested dataset.
  • For example: If the maximum value of the incremental column is "2026-04-07T00:00:00+00:00". Then, in the next run, only records with a value greater than this timestamp will be ingested. This process ensures that only new or updated records are processed and ingested.


Key Considerations:

Select a Suitable Incremental Column:
 - Choose a column that accurately reflects updates, such as the Last Modified Date or System Modified Date.
Avoid Using Columns That:
 - Do not update consistently
 - Contain null or inconsistent values
Potential Consequences of Incorrect Column Selection:
 - Missing records, resulting in data loss

 
Дополнительные ресурсы

Caching or Acceleration in Data Federation

Номер статьи базы знаний

005318396

 
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Salesforce Help | Article