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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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 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

Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.

Topic 7

Data Integration Code Ability: This section evaluates proficiency with common Marketing Cloud Intelligence functions, enabling Salesforce marketing professionals to integrate diverse data sources effectively for comprehensive marketing intelligence.

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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q41-Q46):

NEW QUESTION # 41
Which two statements are correct regarding LiteConnect?

A. Data coming from LiteConnect cannot be harmonized with the rest of the workspace data via the harmonization center at a later step.
B. It does not require any identification of entities, keys or any other categorization.
C. All of the dimensions mapped within a LiteConnect data stream are considered overarching entities.
D. The dataset does not conform to the standard data model

Answer: B,D

Explanation:
LiteConnect is a feature in Salesforce Marketing Cloud Intelligence that allows users to bring external data into the platform quickly and easily. Here are the correct statements regarding LiteConnect:
* A.LiteConnect allows for a quick setup by not requiring detailed identification of entities, keys, or categorization. Users can upload files without having to conform to the standard data model, which speeds up the process of data integration.
* B.With LiteConnect, datasets are uploaded in their native format and do not conform to the standard data model of Marketing Cloud Intelligence. This means that the original structure of the dataset is maintained, and there is no need for extensive transformation or mapping upon the initial data import.
For C and D: While LiteConnect datasets might not conform to the standard data model initially, there are capabilities within Marketing Cloud Intelligence to further categorize and harmonize this data if needed.
Therefore, C is not entirely correct, and D is incorrect because harmonization can indeed occur at a later step.

NEW QUESTION # 42
A client provides the following three files:
File A:

File B:

File C:

File A was uploaded using the Ads data stream type.
The client would like to create this view (data from Files B & C) in Datorama:

Which proposed solution would cause a false connection between the two files?

A. Custom classification
B. VLOOKUP in Data Stream C. Vlookup will return "MB Name"
C. VLOOKUP in Data Stream B. Vlookup will return "Day" and "Installs"
D. Data Classification

Answer: C

Explanation:
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.

NEW QUESTION # 43
The following file was uploaded into Marketing Cloud Intelligence as a generic dataset type:

The mapping is as follows:
Day - Day
Web_site_source - Main Generic Entity Attribute 01
Page Views - Generic Metric 1
*Note that 'web_site_key' and 'web_site_name' are NOT mapped.
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:
In Marketing Cloud Intelligence, when a file is uploaded as a generic dataset type and mapped accordingly, each unique combination of the mapped fields results in a separate row in the database. The file in question has been mapped with 'Day' to 'Day', 'Web_site_source' to 'Main Generic Entity Attribute 01', and 'Page Views' to 'Generic Metric 1'. The 'web_site_key' and 'web_site_name' are not mapped and thus, won't affect the row count.
Since there are 4 unique combinations of the mapped fields in the uploaded file (each day and source combination is unique), Marketing Cloud Intelligence will store 4 rows after ingestion, corresponding to each unique combination of 'Day' and 'Web_site_source'.

NEW QUESTION # 44
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:

The client suggested to create, without any mapping manipulations, several patterns via the harmonization center that will generate two Harmonized Dimensions:
Exam ID
Exam Topic
Given the above information, which statement is correct regarding the ability to implement this request with the above suggestion?

A. The above Patterns setup will not work for this use case.
B. The solution will work - the client will be able to view Exam Topic with Email Sends.
C. Only if 5 different Patterns are created, from 5 different fields - the solution will work.
D. The Harmonized field for Exam ID is redundant. One Harmonized dimension for Exam Topic is enough for a sustainable and working solution

Answer: D

Explanation:
If the harmonization logic consistently associates a single Exam Topic with each Exam ID across all data sources, then creating two harmonized dimensions may be unnecessary. One harmonized dimension for Exam Topic would suffice because it inherently carries the Exam ID's uniqueness within it. The harmonized dimension for Exam Topic would allow the client to slice the data by Exam Topic values, fulfilling the requirement.

NEW QUESTION # 45
An implementation engineer has been asked by a client for assistance with the following problem:
The below dataset was ingested:

However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type' is 4.
What could be the reason for this discrepancy?

A. The aggregation function is set as AVG
B. The aggregation function is set as LIFETIME
C. The measurement 'Clicks' is set as a percentage.
D. A mapping formula was populated, indicating not to bring Type! values.

Answer: A

Explanation:
The discrepancy of 'Clicks' being reported as 4 for 'Type1' when the sum of clicks in the dataset for 'Type1' is 8 (2 on 02/02/2021 and 6 on 03/02/2021) suggests that the aggregation function used in the pivot table is set to average (AVG) rather than sum. Salesforce Marketing Cloud Intelligence allows setting different aggregation functions for metrics, and setting it to average would result in such a discrepancy when more than one entry for the same type exists. Reference: Salesforce Marketing Cloud Intelligence documentation on custom measurements and data aggregations explains how to set and understand different aggregation functions.

NEW QUESTION # 46
......

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