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

In the context of Marketing Cloud Intelligence, when building a calculated dimension, you can typically use:

B. Mapped dimensions: These are dimensions that have been brought into Marketing Cloud Intelligence through the data integration process and have been mapped to a known schema or model.

C. The EXTRACT function: This function can be used to dynamically create dimensions by extracting values from a mapped dimension or measurement.

E. Mapped measurements: Similar to mapped dimensions, these are quantitative data points that have been integrated into the platform and can be referenced in calculations.

Calculated dimensions (D) and the VLOOKUP function (A) are not typically used within the expression for a calculated dimension. Calculated dimensions are usually an output, not an input, and VLOOKUP is a function typically used to enrich or connect data, not within the definition of a calculated dimension itself.

To create both 'Platform' and 'Line of Business' fields using Patterns in the Harmonization Center without mapping manipulations, the engineer would need to create separate patterns for each data source mentioned. According to the provided images:

One pattern for LinkedIn Ads, to extract the 'Campaign Name' at position 4 for the Platform and 'Media Buy Name' at position 7 for Line of Business.

One pattern for AdRoll, to extract 'Media Buy Name' at position 3 for Platform and at position 2 for Line of Business.

One pattern for Google Analytics, which seems not required for the Platform but could apply if the Line of Business extraction is necessary, although it states N/A.

Hence, a minimum of 3 patterns would be necessary to create the fields required.

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.