Marketing-Cloud-Intelligence Exam Dumps : Marketing Cloud Intelligence Accredited Professional (AP-215)

Since Data Stream C is considered the source of truth for both dimensions and measurements, it should be set as the parent data stream. This is because the parent data stream is used as the primary source for hierarchical and attribute data within a parent-child relationship setup. As the source of truth, Data Stream C will provide the foundational data upon which the other streams can be aligned and will ensure consistency and accuracy across the linked data.

In Marketing Cloud Intelligence, data stream types are templates that define how data should be structured within the system. Each data stream type:

B. Includes at least one entity, which is a fundamental component of the data stream and represents a collection of related data points.

D. Has its own main entity, which is the primary focus of that particular data stream type and serves as the central point of reference for the associated data.

E. Contains its own unique set of measurements that are specific to the type of data being captured within that stream. These measurements represent quantitative data that can be analyzed within the context of the main entity and other dimensions present in the data stream.

A is incorrect because not every data stream type includes the Media Buy entity—this is specific to certain types of advertising data streams. C is incorrect because not all data stream types share at least one mutual measurement; measurements are typically unique to the data stream's focus and purpose.

Option #2: It suggests using the 'SUM' function to aggregate the 'Site Revenue' for each 'Site Key'. This is necessary to ensure that when aggregated by date, 'Site Revenue' should return the total sum of the highest revenue for all sites.

Option #4: It indicates changing the Aggregation Function of Revenue to 'MAX' within Data Stream C. This ensures that for a given 'Site Key', the highest revenue value is selected, which is correct for individual site revenue determination.

Combining Option #2 and Option #4 will provide the desired result:

For an individual 'Site Key', it will give the highest revenue (using MAX aggregation in Option #4).

When aggregating by date across all 'Site Key's, it will sum the highest revenues (using the SUM function in Option #2).