Marketing Cloud Intelligence Accredited Professional Exam study guide: exam Marketing-Cloud-Intelligence real vce collection

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Marketing-Cloud-Intelligence Exam Papers - Marketing-Cloud-Intelligence Technical Training

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	Mapping: Marketing professionals will focus on Marketing Cloud Intelligence ingestion capabilities, assessing knowledge of data mapping processes and outcomes critical to efficient data organization.
Topic 4	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 5	Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
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	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.

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q28-Q33):

NEW QUESTION # 28
A client's data consists of three data streams as follows:
Data Stream A:

A. Update Attributes and Hierarchies
B. It doesn't matter. As long as Data stream A is set as a Parent', the rest of the Data Updates Permissions are irrelevant.
C. Update Attributes
D. Inherit Attributes and Hierarchies

Answer: D

Explanation:
For the client's data consisting of three data streams, setting Data Stream A as the Parent allows for inheriting attributes and hierarchies from it to the child data streams. This ensuresconsistency across the data streams, making it possible to analyze the data collectively, using the structure and attributes defined in the Parent data stream.

NEW QUESTION # 29
Which option will yield the desired result:?

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

Answer: B

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 'Campaign Key' 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 # 30
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 be checked in Data Stream C
B. It should be checked in Data Stream A
C. It should be checked in Data Stream B
D. It should not be checked in any of the three Data Streams.

Answer: A

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 # 31
Animplementation engineer has been provided with 4 different source files: 03m 16s
1. Twitter Ads
2. Creative Classification
3. Placement Classification
4, Campaign Category Classification
The main source is Twitter Ads (which includes various fields and KPIs), and the rest are classification files that connect to Twitter Ads and enrich different fields within it.
The connections between the files are described as follows:
1st Party Creative Classification
File structure/headers:

Creative ID - links back to Creative Key (Twitter Ads)
1st Party Placement Classification &
File structure/headers:

Category - links back to Campaign Category (Twitter Ads)
Which proposed solution meets the client's requirements for the above use case?

Answer: C

Explanation:
For the given use case, where the Twitter Ads data stream needs to be enriched with classifications from three other sources, the correct implementation would involve creating links between the various fields across these files.
Option A is correct because it shows the correct usage of the fields from the classification files:
* "Creative ID" in the Creative Classification file is linked to the "Creative Key" in the Twitter Ads data, allowing for enrichment with creative details.
* "Placement ID" in the Placement Classification file is linked to a corresponding field in the Twitter Ads data, allowing for placement details to be added.
* "Category" in the Campaign Category Classification file is linked back to "Campaign Category" in the Twitter Ads data, thus enriching the campaign data with the correct categories.
This configuration correctly uses VLOOKUP to enrich the Twitter Ads data stream with additional details from the classification files, aligning with best practices for data integration and enrichment in Marketing Cloud Intelligence.

NEW QUESTION # 32
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: D

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 # 33
......

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MARKETING CLOUD INTELLIGENCE ACCREDITED PROFESSIONAL EXAM STUDY GUIDE: EXAM MARKETING-CLOUD-INTELLIGENCE REAL VCE COLLECTION

Marketing Cloud Intelligence Accredited Professional Exam study guide: exam Marketing-Cloud-Intelligence real vce collection