An AEP expert has been tasked with a last-minute request to send a campaign. The AEP expert needs to upload a CSV file with the customer list that will be affected through the campaign, create the segments based on a briefing, and share those segments with Adobe Campaign and Facebook Custom Audiences. The brief also includes the segment volumes.
Before sharing the segments, the AEP expert needs to make sure that the segment volumes match the briefing.
What should the AEP do right after creating the segments to get the volumes?
To get the segment volumes in Adobe Experience Platform, the AEP expert can use the Profiles over time graph that appears on the segment details. The Profiles over time graph shows the number of profiles that match the segment criteria over time. The AEP expert can use this graph to verify that the segment volumes match the briefing.
After creating the Entity Relationship (Diagram (ERD) of the data sources that will be connected into an AEP implementation for a utility company, the service details (including information such as name, cost type, and category) appear multiple times across different entities (for example, in the transactional events and m the customer profile details).
When designing the XDM data model for that ERD, the data architect and the business stakeholders validate that the service details information must be included at both levels, record, and time series. The service details will be used multiple times within the same structure.
How should the service details be defined in the AEP data model to make it consistent and re-usable?
A data engineer is ingesting time-series data in CSV format from a CRM system. The source data contains a "subscription" field that contains what level of subscription the customer has purchased.
The data is ingested into a target field called "subscriptionLevel". which is an enum field that accepts the following values: "Lite*. "Standard", and "Pro''.
The data engineer knows that the CSV files contain some rows that do not conform to the above enum. Instead of rejecting those rows, the data engineer wants to transform non-conforming fields to "Standard".
Which mapping function(s) will accomplish this?
you can use Data Prep functions to compute and calculate values based on what is entered in source fields. The iif function returns one value if a condition is true and another value if it is false.
https://experienceleague.adobe.com/docs/experience-platform/data-prep/functions.html?lang=en
A B2B business (the client) is migrating its data warehouse (DWH) solution to AEP. Currently, they are using what they call Recipient ID as the main identifier to recognize client employees. That Recipient 10 is generated inside the DWH. That solution will not be available once AEP is live, so the solution architect needs to consider potential alternatives.
After working with the client lead and a data engineer, the solution architect identifies that a combination of Company ID and Hashed Employee Email would be a good replacement for the Recipient ID to make it more unique.
How can the solution architect generate that identity within AEP?
A data engineer must set up a Streaming Connection with new authentication via the AEP Ul to stream non XDM data into an existing Dataset. How should the data engineer proceed?
