B.

Creating data policies and applying them to datasets and fields.

D.

Reviewing data, datasets, and data samples to apply and manage metadata usage labeling.

Explanation: According to the Adobe documentation, a Data Steward is a role that is responsible for ensuring data quality, compliance, and governance across the organization. Some of the main tasks of a Data Steward include creating data policies and applying them to datasets and fields, reviewing data, datasets, and data samples to apply and manage metadata usage labeling, monitoring data quality issues and resolving them, etc.

D.

The majority of browsers on the website are not authenticated.

Explanation: The most likely explanation for the dramatic drop in segment size is that the majority of browsers on the website are not authenticated. This means that they do not have a loyalty account or a unique identifier that can be matched with the gender attribute from the loyalty system. Therefore, they are excluded from the segment that ANDs the gender attribute with the browsing behavior. To increase the segment size, the retailer could use other methods to identify or infer the gender of anonymous browsers, such as cookies, device IDs, or third-party data.

B.

Timestamp ordered

Explanation: According to the Adobe documentation, timestamp ordered is a merge method that can be used to create a custom merge policy in Adobe Experience Platform for an upcoming use case to ensure profile attributes take precedence from latest datasets and are applied across all datasets automatically. Timestamp ordered merge method prioritizes profile attributes based on their ingestion timestamp, with newer values taking precedence over older values. Timestamp ordered merge method also applies globally across all datasets within a tenant.

B.

File based destinations

A.

Primary identity

Explanation: According to the Adobe documentation, primary identity is an identity that must be set in a schema in order to use it in Real-Time Customer Profile. Primary identity is an identity that uniquely identifies each profile within a dataset and across datasets within a tenant. Primary identity can be either predefined or custom, but it must have cardinality of one-to-one or many-to-one.

B.

Self-serve applications

D.

Applications integrated with Privacy Service

Explanation: According to the Adobe documentation, self-serve applications are applications that allow users to create and manage their own Privacy Service requests, such as Adobe Experience Platform, Adobe Campaign Standard, and Adobe Target. Applications integrated with Privacy Service are applications that have built-in integrations with Privacy Service and can automatically process requests, such as Adobe Audience
Manager, Adobe Analytics, and Adobe Experience Manager.

D.

Schema

Explanation: According to the Adobe documentation, DULE labeling is a framework that allows applying data usage labels (DULs) to data fields based on their usage category (Descriptive, Underlying, Linked, or Extracted). DULs can be applied at the schema level, which means they will propagate to all datasets and fields that use that schema.

A.

Dataset activity

B.

Source's dataflow activity

Explanation: According to the Adobe documentation1, dataset activity and source’s dataflow activity are two places where ingestion errors can be viewed. Dataset activity shows the status of each batch that is ingested into a dataset, including any errors or warnings. Source’s dataflow activity shows the status of each source connection run, including any errors or warnings.