Description - Ability to clean up batches which have been ingested into the datalake. Why is this feature important to you -  This feature is important to clean up batches which have been ingested into the the AEP datalake which may no longer be relevant. How would you like the feature to work -  A...

Hello @ShivaniM    A null values in a database / data warehouse is really an indicator data does not exist in the column for the record.    When data is ingested into the Adobe RTCDP platform you will need to consider how to evaluate the presence of null from an external source.     When data does n...

A streaming segment can look back up to 7 days for a segment evaluation.  Edge is limited to a 24 hr window.  Anything past 7 days is considered a batch evaluation.

with the case noted above since the segment was created after the event occurred, the streaming segment would be evaluated by the batch_segmentation process.   Since event occurred before the segment was created I do not believe it would be realized in the segment.  If the event occurs after the seg...

Description - Provide visibility of the active user connection(s) to the AEP datalake. Why is this feature important to you - Feature is important for administration of the AEP sandbox to understand what the active connections to the datalake How would you like the feature to work - Provide an API ...

Hi @Michael_Soprano    The way you can think of streaming segment is the evaluation of the segment will occur on the incoming hit of data.     If data is ingested for the profile the segment will evaluated the profile to determine the qualification for the segment.  The streaming segment would be ev...

Hello @SaravananKa    You can use the /GET Profile Entity API to return the segment membership of a profile.   https://experienceleague.adobe.com/en/docs/experience-platform/profile/api/entities.   example:  curl -X GET \'https://platform.adobe.io/data/core/ups/access/entities?schema.name=_xdm.conte...

Hi @RyanMoravick    There are few way to get at the audience.     You can build an initial audience where there is at least 1 purchase event and then build exclusion logic of when there is more than 1 purchase event.   you could also use a computed attribute to find the most recent purchase event to...