Salesforce Marketing-Cloud-Intelligence Exam With Confidence Using Practice Dumps

In Marketing Cloud Intelligence, when linking two data streams, the parent data stream (File A) provides the main structure. Since 'Override Media Buy Hierarchies' is checked for File A, the hierarchies from File B will be aligned with File A. Given 'Data Updates Permissions' set for file B as 'Update Attributes and Hierarchy', this means that attributes and hierarchy will be updated in the parent file based on the child file (File B), but the child file’s metrics won’t be associated with the parent file’s date.

Hence, when filtering on the entire date range (1-30/8), the resulting view will align with the structure of the parent data stream, showing the KPIs (‘Tasks Completed’ from File A and ‘Tasks Assigned’ from File B) alongside the employee names and squads from the respective files. Since the employee IDs align, the data can be linked properly. However, since the dates do not align (File A data is from 01/08/2019 and File B from 15/08/2019), only attributes from File B will be updated without date association.

The result will look like Option C, where the employee names are corrected based on File B's data, the squads are added from File B, and the tasks_completed and tasks_assigned are displayed from their respective files. The tasks_assigned from File B are shown without date association as File B's date doesn't match with File A's.

In Marketing Cloud Intelligence, discrepancies between the number of rows uploaded and the number of rows present in the source file can be caused by several factors. If all mapped measurements for a row are zero, that row may be excluded from the upload, as it does not contribute to the analytics. Additionally, if the main entity, which acts as the primary identifier for records, is not mapped, the system cannot correctly ingest the data as it lacks the necessary reference to organize and store the information.

For the field 'Magician', the engineer is required to follow a logic that extracts a value from 'Campaign Name' and checks against a validation list for specific values ('Messi' or 'Ronaldo'). If those values are not found, it should instead extract from 'Media Buy Name'. To accomplish this, the engineer should:

Use the created Pattern for 'Campaign Name'.

Create a second Pattern for 'Media Buy Name' to capture the fallback values.

Apply two Classification Rules to the Harmonized Dimension: one for the value 'Messi' and another for 'Ronaldo'. This is to check the extracted 'Campaign Name' against these specific values.

These steps ensure that the 'Magician' field will be populated with the correct values from the respective data streams following the specified logic.