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Exam Sample Marketing-Cloud-Intelligence Questions & New Marketing-Cloud-Intelligence Test Topics

Marketing-Cloud-Intelligence practice test material is in line with the content of the actual Salesforce Marketing-Cloud-Intelligence certification test. Before buying Marketing-Cloud-Intelligence exam dumps, you can test its features with a free demo. If you get help from updated Marketing-Cloud-Intelligence questions, you can easily clear the Marketing Cloud Intelligence Accredited Professional Exam (Marketing-Cloud-Intelligence) test in one go. After receiving input from thousands of professionals worldwide, DumpsReview has developed its Marketing-Cloud-Intelligence exam study material. After making a payment, clients will get up to three months of free Salesforce Marketing-Cloud-Intelligence exam questions updates as well.

Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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 4

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

Topic 5

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 6

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 7

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 8

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 9

QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q12-Q17):

NEW QUESTION # 12
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.
Assuming the data was ingested properly and the Parent Child was created correctly according to the client's requirements, what is the total Impressions value for Campaign Key 'CK_3'?

A. N-A
B. 0
C. 1
D. 2

Answer: C

Explanation:
Assuming that Data Stream A is set correctly with parent-child relationships:
To find the total impressions for Campaign Key 'CK_3', you would look in Data Stream A, since it contains the 'Impressions' metric.
As per the provided data, Campaign Key 'CK_3' has 100 impressions.

NEW QUESTION # 13
An implementation engineer is requested to extract the first three-letter segment of the Campaign Name values.
For example:
Campaign Name: AFD@Mulop-1290
Desired outcome: AFD
Other examples:

Which formula will return the desired values?

A. LEFT(EXTRACT(csv[campaign_name'}/-',1),3)
B. EXTRACT(csv[campaign_name!;@',1)
C. EXTRACT(csv[campaign_name'],-,0)
D. EXTRACT(EXTRACT(csv['campaign_name]]/@',1),-,0)
E. LEFT(EXTRACT(csy['campaign_name]],~',0),3)

Answer: B

Explanation:
The EXTRACT function is used to split a string based on a delimiter and return the segment at the specified position. The campaign names are structured with the segment of interest followed by an '@' sign. Therefore, the formula needs to extract the segment before the '@'.
* The correct formula is: EXTRACT(csv['campaign_name']; '@', 1). This will take the 'campaign_name' field, split it at the '@' sign, and return the first segment (position 1), which is the three-letter code that is required. The other options are incorrect because they do not properly specify the delimiter and the segment position in the way needed to achieve the desired outcome.

NEW QUESTION # 14
Which three entities and/or functions can be used in an expression when building a calculated dimension?

A. The VLOOKUP function
B. Mapped measurements
C. Mapped dimensions
D. Calculated dimensions
E. The EXTRACT function

Answer: B,C,E

Explanation:
In the context of Marketing Cloud Intelligence, when building a calculated dimension, you can typically use:
* B. Mapped dimensions: These are dimensions that have been brought into Marketing Cloud Intelligence through the data integration process and have been mapped to a known schema or model.
* C. The EXTRACT function: This function can be used to dynamically create dimensions by extracting values from a mapped dimension or measurement.
* E. Mapped measurements: Similar to mapped dimensions, these are quantitative data points that have been integrated into the platform and can be referenced in calculations.
Calculated dimensions (D) and the VLOOKUP function (A) are not typically used within the expression for a calculated dimension. Calculated dimensions are usually an output, not an input, and VLOOKUP is a function typically used to enrich or connect data, not within the definition of a calculated dimension itself.

NEW QUESTION # 15
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. 0
B. 1
C. 2
D. 3

Answer: A

Explanation:
Based on the Opportunity file, the Opportunity Stage of 'Interest' occurs 3 times across unique Opportunity Keys. Since the pivot table is filtered to present the entire month of January and theOpportunity Stage 'Interest' is listed three times with different Opportunity Keys, the count of opportunities in the 'Interest' stage would be
3.

NEW QUESTION # 16
An implementation engineer is requested to extract the second position
of the Campaign Name values.
The Campaign values consist of multiple delimiter types, as can be
seen in the following example:
Campaign Name: Ad15X2w&Delux_wal90
Desired value: Delux
Which three harmonization methods will achieve the desired outcome?

A. Vlookup 0
B. Patterns
C. Mapping formula
D. Data Fusion
E. Calculated Dimensions

Answer: B,C,E

Explanation:
To extract specific elements from a string in Marketing Cloud Intelligence, such as the second position of a Campaign Name with multiple delimiters, several harmonization methods can be employed:
Calculated Dimensions: These allow for the creation of custom dimensions using expressions or formulas that manipulate existing data. A calculated dimension can be designed to parse and extract segments of a string based on delimiters.
Patterns: This method involves defining a pattern or regex (regular expression) that matches and isolates the desired portion of the string. Patterns are highly effective for strings with complex structures and varying delimiter types.
Mapping Formula: Similar to calculated dimensions, mapping formulas provide a way to apply a transformation or extraction rule to data fields directly within data streams, enabling targeted data extraction like the desired 'Delux' from the Campaign Name.
These methods enable the implementation engineer to accurately segment and extract the needed data from complex string fields efficiently.

NEW QUESTION # 17
......

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