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A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.

What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?

• A. Scalability
• B. Use of code
• C. Processing (processing time when loading relevant data streams)
• D. Ease of Maintenance
• E. Performance (Performance when loading a dashboard page)

Which two statements are correct regarding the Parent-Child configuration?

• A. Parent-Child allows sharing both dimensions and measurements
• B. A Parent-Child cannot be configured between an Ads data stream type and a Conversion Tag one.
• C. Parent-Child links different tables based on shared key values
• D. Parent-Child configurations can cause performances issues

Source 3:

Via the harmonization Center, the Client has created Patterns and applied a classification rule using source 2.
While performing QA, you have spotted that the final value of clicks for Product Group Ais 10, where it should've been i5.

How can an implementation engineer fix this discrepancy?

• A. Leave the "Case Sensitive" checkbox in the data classification unchecked
• B. Uncheck the "Case Sensitive" checkbox in the data classification
• C. Toggle the 'Structure Compliant' OFF.
• D. Upload both source 1 and 3 to the same data stream type in order to be able to generate Patterns from them.

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?

• A. Create a Web Analytics Site Source custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
• B. Create a Web Analytics Site custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
• C. Within both files, map the desired value to Custom Classification Key as follows Salesforce Marketing Cloud: map entire Message Key to Custom Classification Key.
  Google Analytics: map the extraction logic to Custom Classification Key.
• D. Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.

A technical architect is provided with the logic and Opportunity file shown below:
The opportunity status logic is as follows:
For the opportunity stages "Interest", "Confirmed Interest" and "Registered", the status should be "Open".
For the opportunity stage "Closed", the opportunity status should be closed Otherwise, return null for the opportunity status

Given the above file and logic and assuming that the file is mapped in a GENERIC data stream type with the following mapping:
"Day" - Standard "Day" field
"Opportunity Key" > Main Generic Entity Key
"Opportunity Stage" - Generic Entity Key 2
"Opportunity Count" - Generic Custom Metric
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on January (entire month). What is the number of opportunities in the Interest stage?

• A. 1
• B. 0
• C. 2
• D. 3