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. Create a XDM Schema
• B. Create a XDM Class
• C. Create a Field Group
• D. Create a Data Type

When sending data through the RESTful API. how can data engineers make sure the payload being sent is formatted property in real time?

• A. As long as the data matches the pre-defined SXM schema, records in the payload pass
• B. All data is ingested and query services reporting identify any records that do not pass custom validation rules.
• C. Leveraging synchronous validation, data engineers can review error messages for records that fail validation.
• D. Leveraging asynchronous validation, data engineers can review error messages for records that fail validation.

A data architect creates two XDM schemas: Schema A and Schema B.
What are the two requirements for defining a schema relationship so that Schema A references Schema B for use in segmentation? (Choose two.)

• A. Schema A and Schema B must each have datasets associated with them.
• B. Schema A and Schema 6 must each be enabled for Real-time Customer Profile.
• C. Schema A and Schema B must each have a primary identity.
• D. Schema A must belong to the same schema class as Schema B.
• E. Both schemas should have the same fields marked as identities.

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?

• A. iif(subscription.equals("Lite") || subscription.equals("Standard") || subscriptionequalsfPro").
  subscription. "Standard")
• B. iif(subscription.equals("Lite") &&subscriptiorvequ3ls("Standard") && sub$ctiption.eqoals("Pro").
  subscription. el$e("5tandard"))
• C. iif(subscription.noiEquals(*Lite" || "Standard" || "Pro"), subscription, subscription, replacestrf
  "Standard"))
• D. iif(subscription.notEquals("Lite") || subscription.notEqualsl "Standard") || subscription.notEquatsCPro').
  'Standard', subscription)

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?

• A. Destination > Streaming > HTTP API > New Account > Select Data > Map Fields to XDM Select Dataset > Finish
• B. Sources > Streaming > HTTP API > Add Data > New Account > Select Data > Map Fields to XDM > Select Dataset > Finish
• C. Sources > Streaming > HTTP API > Add Data > New Account > Select Data > Map Fields to XDM > New Dataset > Finish
• D. Sources > Streaming > HTTP API > New Account > Add Data > Select Data > Select Dataset > Finish