A marketer wants 10 create a segment that qualities profiles from all datasets that are enabled for profile. The use case for the segment is for activation to advertising destinations.
Based on the options for ID stitching and merge method respectively, which type of merge policy is appropriate for this use case?

A marketer recently set up an Amazon S3 cloud storage destination. The last successful flow for the destination exported 12 million records. in the Amazon S3 bucket, how will the export be presented to the marketer?

There are two existing entities in the Real-time Customer Profile store: one profile record and one event.

Both the event schema and profile schema have "email" as the primary identity. The _id is used to identify unique events.
Later, a data engineer ingests one additional profile fragment and another event:
Profile: ("email": "[email protected]*. "favBrand': "Adobe")
Event: {''_id": '5000". "email": "[email protected]". "purchase": "Photoshop 2021") What will the profile attributes and event look like when doing a profile [email protected]?
A)

B)

C)

D)

A data engineer it running some tests And tending in event data
How should the data engineer validate that the event is properly attributed to the correct profiler

A data engineer is ingesting website data via CSV that represents a future hotel reservation.

Each field is mapped to the corresponding target field below:
"fullName": "string", 'crmld": "string", "email": "string", "swyDate": "dateTime", "_id": "string" Upon mapping the data, the mapping step fails with an error.
What is the possible cause of this error?