Free Salesforce Marketing Cloud Intelligence Accredited Professional (AP-215) Exam Dumps June 2026

To QA the Parent-Child relationship setup between Google Campaign Manager and IAS data sources, it is essential to query fields that are common to both sources and that are relevant to the relationship. 'Media Buy Type' and 'Media Buy Name' are common identifiers between the two datasets. 'Impressions' from the Google Campaign Manager and 'Analyzed Impressions' from the IAS data are the metrics that should be compared to ensure they match or correlate as expected due to the Parent-Child relationship. The QA process involves checking that the data is correctly aligned and that the metrics from the parent source (Google Campaign Manager) are properly related to the metrics from the child source (IAS). Reference: Salesforce Marketing Cloud Intelligence documentation on data integration, Parent-Child relationships, and QA procedures for data setup.

The goal is to obtain a 'Campaign Planned Clicks' value per Campaign, not accumulated by Media Buy keys. Option 1 (SUM aggregation function) would sum all the 'Campaign Planned Clicks' across Media Buy keys which would not yield the unique value per Campaign. Similarly, Option 5 (AVG aggregation function at Campaign Key level) would incorrectly average the values. Both options do not provide a way to return a singular 'Campaign Planned Clicks' value for each Campaign.

To meet the client's requirement of slicing measurements by 'Exam Topic' values, an Implementation Engineer should use Custom Classification. This feature allows different Exam IDs to be classified into their respective Exam Topics, ensuring that data from all sources can be accurately harmonized and analyzed based on these topics.

To achieve a final view of Product Group alongside Clicks and Sign Ups, we should use:

Option A:

Custom Classification: By using a Custom Classification key populated with the extraction of the Media Buy Name in Source 1, we can then map 'Product' in Source 2 to this key and 'Product Group' to a Custom Classification level. This will allow for grouping and analysis by Product Group, as well as enable the desired view to be created.

Option D:

Harmonization Center: With patterns from Sources 1 and 3, we can create a harmonized dimension 'Product'. Then, by applying a Data Classification rule using Source 2, we can enhance the harmonized dimension. This allows us to align 'Product Group' with the 'Product' from Sources 1 and 3, facilitating an integrated view of Clicks and Sign Ups by Product Group.

With File A uploaded using the Ads data stream type, the client wishes to create a view incorporating data from Files B & C.

A false connection would occur if VLOOKUP in Data Stream B is used incorrectly to return ''Day'' and ''Installs''. In this scenario, VLOOKUP might inaccurately link data based on MB Name between File B and File A or File C, which do not have a 'Day' field to correctly join on. Moreover, 'Installs' data in File B doesn't exist, so VLOOKUP cannot correctly return this information. The correct method would be to use the 'Media Buy New Name' to link File B and File C since they both have this field, ensuring accurate connection and avoiding data mismatches or false connections.