100% PASS QUIZ UPDATED SALESFORCE - VALID MARKETING-CLOUD-INTELLIGENCE TEST PREP

100% Pass Quiz Updated Salesforce - Valid Marketing-Cloud-Intelligence Test Prep

100% Pass Quiz Updated Salesforce - Valid Marketing-Cloud-Intelligence Test Prep

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

TopicDetails
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
  • QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 3
  • 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 4
  • 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 5
  • 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 6
  • 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 7
  • 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 8
  • Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.
Topic 9
  • Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 10
  • 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 11
  • 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 (Q35-Q40):

NEW QUESTION # 35
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.
How should the "Override Media Buy Hierarchies" checkbox be set in order to meet the client's requirements?

  • A. It should not be checked in any of the three Data Streams.
  • B. It should be checked in Data Stream C
  • C. It should be checked in Data Stream A
  • D. It should be checked in Data Stream B

Answer: B

Explanation:
If Data Stream C is the source of truth, the "Override Media Buy Hierarchies" checkbox should be checked for Data Stream C.
This means that the hierarchy defined within Data Stream C will take precedence over any other media buy hierarchies present in Data Streams A or B. By doing so, it enforces that the hierarchy from the source of truth (Data Stream C) is used throughout the dataset, maintaining the integrity of the hierarchical relationships as defined by the most reliable data source.


NEW QUESTION # 36
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.
The client would like to have a "Site Revenue" measurement.
This measurement should return the highest revenue value per Site, for example:
For Site Key 'SK_C_2', the "Site Revenue" should be $7.00.
When aggregated by date, the "Site Revenue" measurement should return the total sum of the results of all sites.
For example:
For the date 1 Apr 2020, "Site Revenue" should be $11.00 (sum of Site Revenue for Site Keys 'SK_C_1' ($4.00) and 'SK_C_2' ($7.00))

Which options will yield the desired result;

  • A. Option #2 & Option #3
  • B. Option #1 & Option #3
  • C. Option #1 & Option #4
  • D. Option #2 & Option #4

Answer: D

Explanation:
Option #2: It suggests using the 'SUM' function to aggregate the 'Site Revenue' for each 'Site Key'. This is necessary to ensure that when aggregated by date, 'Site Revenue' should return the total sum of the highest revenue for all sites.
Option #4: It indicates changing the Aggregation Function of Revenue to 'MAX' within Data Stream C.
This ensures that for a given 'Site Key', the highest revenue value is selected, which is correct for individual site revenue determination.
Combining Option #2 and Option #4 will provide the desired result:
For an individual 'Site Key', it will give the highest revenue (using MAX aggregation in Option #4).
When aggregating by date across all 'Site Key's, it will sum the highest revenues (using the SUM function in Option #2).


NEW QUESTION # 37

Which option will yield the desiredresult:?

  • A. Option 2
  • B. Option 1
  • C. Option 3
  • D. Option 4

Answer: D

Explanation:
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 'CampaignKey' 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.


NEW QUESTION # 38
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
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan
7th-11th.Which option reflects the stage(s) the opportunity key 123AA01 is associated with?

  • A. Interest & Registered
  • B. Confirmed Interest & Registered
  • C. interest
  • D. Confirmed interest

Answer: A

Explanation:
Filtering the pivot table on January 7th-11th, we see that the Opportunity Key 123AA01 appears on January
6th with the stage 'Interest' and then on January 10th with the stage 'Registered'. Even though the 'Interest' stage is not within the filtered dates, it is the initial stage of the opportunity, so it should be counted along with the 'Registered' stage which falls within the filter range.


NEW QUESTION # 39
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(csy['campaign_name]],~',0),3)
  • B. EXTRACT(EXTRACT(csv['campaign_name]]/@',1),-,0)
  • C. EXTRACT(csv[campaign_name!;@',1)
  • D. LEFT(EXTRACT(csv[campaign_name'}/-',1),3)
  • E. EXTRACT(csv[campaign_name'],-,0)

Answer: C

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 # 40
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