An implementation engineer is requested to integrate the following files:
File A:

File B:

The client would like to link the two files in order to view the two KPIS (Tasks Completed' and 'tasks Assignmed') alongside'Employee Name' and/or 'Squard'.
A Parent-Child configuration was set between the two.
Which two statements are correct?
In Marketing Cloud Intelligence, joining two files requires a common field to be mapped as the same entity. If 'employee_name' is consistently mapped across both data streams, it can serve as the basis for the join, regardless of whether 'employee_id' is mapped. The choice of which file serves as the Parent stream depends on the use case and the desired reporting structure, but technically, either could serve as the Parent.
Client has provided sample flies of their data from the following data sources:
Google Campaign Manager

Below are the requirements from the client and additional information:
* The sources are linked to each other by shared Media Buy names.
* In addition-to the mutual Media Buys, the sources contain campaign and site values. However, the client would like to see the campaign/site values coming from Google CM and not from Google DV360.
* The source of truth for cost is Google DV360.
As a first step, a Parent-Child relationship was created between the two files, and the following mapping was performed, within both data streams:

Please note:
* All other measurements were mapped as well to the appropriate fields.
* No other mapping manipulations or formulas were implemented.
How many records will the merged table hold?
Since the data sources are linked by shared Media Buy names and all other measurements are mapped to appropriate fields without additional manipulations, each unique Media Buy Name from Google DV360 will pair with its corresponding Media Buy Name in Google Campaign Manager. The number of records in the merged table will equal the number of unique Media Buy Names in Google DV360, provided there is a matching name in Google Campaign Manager. The sample shows 4 unique Media Buy Names in Google DV360, thus resulting in 4 records.
A client has provided you with sample files of their data from the following data sources:
1.Google Analytics
2.Salesforce Marketing Cloud
The link between these sources is on the following two fields:
Message Send Key
A portion of: web_site_source_key
Below is the logic the client would like to have implemented in Datorama:
For 'web site medium' values containing the word ''email'' (in all of its forms), the section after the ''_'' delimiter in 'web_site_source_key' is a 4 digit
number, which matches the 'Message Send Key' values from the Salesforce Marketing Cloud file. Possible examples of this can be seen in the
following table:
Google Analytics:

Salesforce Marketing Cloud:

The client's objective is to visualize the mutual key values alongside measurements from both files in a table.

In order to achieve this, what steps should be taken?
To create a linkage between Google Analytics and Salesforce Marketing Cloud data based on the 'Message Send Key' and a portion of the 'web_site_source_key,' both values need to be harmonized into a common key. This is done by mapping the full Message Send Key from Salesforce Marketing Cloud and the extracted part of the web_site_source_key from Google Analytics to the same Custom Classification Key. This mapping will create a common identifier that can be used to combine the data from both sources for analysis and visualization.
What is the relationship between "Media Buy Key" and "Creative Key?
In Marketing Cloud Intelligence, the 'Media Buy Key' is typically associated with the purchase details of a media campaign, such as the platform, audience, and budget. The 'Creative Key' relates to the specific creative asset used within a campaign, like an image, video, or text. A single media buy can have multiple creative variations to test performance or to target different audiences, leading to a one-to-many relationship.
Which option will yield the desired result:?
Option 4 presents two calculated measurements for 'Group Min Cost' with 'MIN' and 'AVG' aggregations. This approach aligns with the client's need for the minimum and average media cost values. 'Group Min Cost 4 MIN' will calculate the minimum media cost across the 'Media Buy Key', while 'Group Min Cost 4 FINAL' will average these minimum costs at the 'Campaign Key' level. This will yield the desired result where minimum costs are calculated at the Media Buy Key level and then averaged at the Campaign Key level.
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