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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic	Details
Topic 1	Vlookup: This section evaluates proficiency of marketing professionals in Vlookup statements and their properties, ensuring accurate data referencing and streamlined data manipulation for marketing intelligence tasks.
Topic 2	Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 3	Harmonization Center (Patterns Data Classification Validation): Salesforce marketing professionals will learn about the Harmonization Center’s capabilities, including classification rules, validation lists, patterns, and harmonized dimensions to ensure data reliability.
Topic 4	Harmonization Best Practices: Salesforce marketing professionals will analyze harmonization methods, properties, and their advantages and disadvantages, enhancing skills for optimizing data consistency across platforms.
Topic 5	Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.
Topic 6	CRM: This topic tests knowledge of CRM properties and their behavior within Marketing Cloud Intelligence. This knowledge is crucial for syncing customer relationship data with marketing campaigns.
Topic 7	General Functionalities: In this topic, Salesforce marketing professionals will explore core functionalities of Marketing Cloud Intelligence. It measures understanding of platform features critical to data-driven marketing strategies and insights.
Topic 8	Overarching Entities: Salesforce marketing professionals will deepen their understanding of overarching entities, their use cases, and application, crucial for strategic data organization and analysis.
Topic 9	QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 10	Data Fusion: This topic focuses on the use cases and properties of Data Fusion, equipping marketing professionals to merge datasets effectively for comprehensive marketing insights.
Topic 11	Data Update Permissions: This area tests knowledge of permissions and settings related to data updates. It includes understanding parent-child setups and managing the "Source of Truth" for data accuracy.
Topic 12	Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.

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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q56-Q61):

NEW QUESTION # 56
The following file was uploaded into Marketing Cloud Intelligence as a Generic Data Stream type:

The mapping is as follows:
Day - Day
web_site_key -> Main Generic Entity Key
web_site_name -> Main Generic Entity Name
Web_site_source -> Main Generic Entity Attribute 01
Page Views - Generic Metric 1
How many rows will be stored in Marketing Cloud Intelligence after the above file is ingested?

A. 0
B. 1
C. 2
D. 3

Answer: C

Explanation:
With the uploaded file mapped as a Generic Data Stream type, the unique identifier for a row is the combination of 'Day', 'web_site_key', 'web_site_name', and 'Web_site_source'. As 'Day' is mapped to 'Day', 'web_site_key' to 'Main Generic Entity Key', 'web_site_name' to 'Main Generic Entity Name', and 'Web_site_source' to 'Main Generic Entity Attribute 01', each unique combination of these fields will constitute a separate row.
The provided file has 4 unique combinations of 'Day', 'web_site_key', 'web_site_name', and 'Web_site_source', as each line has a unique 'web_site_key' and 'web_site_name'. Consequently, Marketing Cloud Intelligence will store 4 rows, one for each unique combination.

NEW QUESTION # 57
Your client would like to create a new harmonization field - Exam Topic.
The below table represents the harmonization logic from each source.

As can be seen from the table there are in fact two fields that hold a certain connection: Exam ID and Exam Topic. The connection indicates that where an Exam ID is found -a single Exam Topic value is associated with it.
The Client has a requirement to be able to view measurements from all data sources sliced by Exam Topic values as seen in the following example:

Which harmonization feature should an Implementation engineer use to meet the client's requirement?

A. Transformers
B. Parent Chile
C. Custom Classification
D. Calculated dimensions
E. Fusion

Answer: C

Explanation:
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.

NEW QUESTION # 58
A client's data consists of three data streams as follows:
Data Stream A:

* The data streams should be linked together through a parent-child relationship.
* Out of the three data streams, Data Stream C is considered the source of truth for both the dimensions and measurements.
* Data Stream C was set as a 'Parent', and the 'Override Media Buy Hierarchy' checkbox is checked What should the Data Updates Permissions be set to for Data Stream B?

A. There is no difference, all permissions will have a similar effect given the scenario.
B. Update Attributes and Hierarchies
C. Update Attributes
D. Inherit Attributes and Hierarchies

Answer: B

Explanation:
With Data Stream C set as the 'Parent' and 'Override Media Buy Hierarchy' checked:
The appropriate setting for Data Stream B would be 'Update Attributes and Hierarchies'. This setting will ensure that the hierarchy and attributes from the parent data stream (C) are updated based on the child data stream (B) without overwriting the measurement data that the parent is the source of truth for.
The 'Override Media Buy Hierarchy' option checked indicates that the hierarchy of the parent is to be considered as the main one, but the attributes and hierarchy can still be updated from the child data stream, which aligns with option B.

NEW QUESTION # 59
Ina workspace that contains one hundred data streams and a lot of data, what is the biggest downside of using calculated dimensions?

A. Performance
B. Ease of maintenance
C. Ease of setup
D. Scalability

Answer: A

Explanation:
In a workspace with a high number of data streams, such as one hundred, the biggest downside of using calculated dimensions is the performance impact. Calculated dimensions require computational resources to dynamically compute values based on existing data. This can lead to increased load times and slower performance, especially in environments with large amounts of data or complex calculations. This performance degradation is due to the extra processing power needed every time the data is accessed or refreshed, impacting the overall efficiency of data retrieval and analysis operations.

NEW QUESTION # 60
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. 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.
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. 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.
D. Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.

Answer: A

Explanation:
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.

NEW QUESTION # 61
......

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Marketing-Cloud-Intelligence Updated CBT | Marketing-Cloud-Intelligence Exam Simulator Fee

Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Marketing-Cloud-Intelligence Exam Simulator Fee & Marketing-Cloud-Intelligence Relevant Questions

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q56-Q61):

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