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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.

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

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 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

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 6

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 7

Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.

Topic 8

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 9

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 10

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.

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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q43-Q48):

NEW QUESTION # 43
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 # 44
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 Jan 7th - 10th. How many different stages are presented in the table?

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

Answer: A

Explanation:
Based on the Opportunity file and considering the filter dates from January 7th to 10th, the different stages presented are 'Interest', 'Confirmed Interest', and 'Registered'. This makes a total of 3 different stages that would be presented in the pivot table. Salesforce Marketing Cloud Intelligence allows for the creation of pivot tables that can display counts of entities across different dimensions, in this case, Opportunity Stages. Reference to Salesforce Marketing Cloud Intelligence documentation that covers data mapping and pivot table creation would support this conclusion.

NEW QUESTION # 45
Your client provided the following sources:
Source 1:

Source 2:

Source 3:

As can be seen, the Product values present in sources 2 and 3 are similar and can be linked with the first extraction from 'Media Buy Name' in source1 The end goal is to achieve a final view of Product Group alongside Clicks and Sign Ups, as described below:

Which two options will meet the client's requirement and enable the desired view?

A. Parent Child:
All sources will be uploaded to the same data stream type - Ads. The setup is the following:
Source 1: Media Buy Key -- Media Buy Key, extracted product value - Media Buy Attribute.
Source 2: Product - Media Buy Key, Product Group -- Media Buy Attribute.
Source 3: Product - Media Buy Key.
B. Custom Classification: 1
Source 1: Custom Classification key will be populated with the extraction of the Media Buy Name.
Source 2: 'Product' will be mapped to Custom Classification key and 'Product Group' to a Custom Classification level. Exam Timer Source 3: 'Product will be mapped to Custom Classification key. Came
C. Harmonization Center: Patterns from sources 1 and 3 generate harmonized dimension 'Product'. Data Classification rule, using source 2, is applied on top of the harmonized dimension
D. Overarching Entities:
Source 1: custom classification key will be populated with the extraction of the Media Buy Name.
Source 2: 'Product' will be mapped to Product field and 'Product Group' to Product Name.
Source 3: 'Product' will be mapped to Product field.

Answer: B,C

Explanation:
To achieve a final view of Product Group alongside Clicks and Sign Ups, we should use:
Option A:
* Custom Classification: By using a Custom Classification key populated with the extraction of the Media Buy Name in Source 1, we can then map 'Product' in Source 2 to this key and 'Product Group' to a Custom Classification level. This will allow for grouping and analysis by Product Group, as well as enable the desired view to be created.
Option D:
* Harmonization Center: With patterns from Sources 1 and 3, we can create a harmonized dimension
'Product'. Then, by applying a Data Classification rule using Source 2, we can enhance the harmonized dimension. This allows us to align 'Product Group' with the 'Product' from Sources 1 and 3, facilitating an integrated view of Clicks and Sign Ups by Product Group.

NEW QUESTION # 46
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 # 47
A client Ingested the following We into Marketing Cloud Intelligence:

The mapping of the above file can be seen below:
Date - Day
Media Buy Key - Media Buy Key
Campaign Name - Campaign Name
Campaign Group -. Campaign Custom Attribute 01
Clicks -> Clicks
Media Cost -> Media Cost
Campaign Planned Clicks -> Delivery Custom Metric 01
The client would like to have a "Campaign Planned Clicks" measurement.
This measurement should return the "Campaign Planned Clicks" value per Campaign, for example:
For Campaign Name 'Campaign AAA", the "Campaign Planned Clicks" should be 2000, rather than 6000 (the total sum by the number of Media Buy keys).
In order to create this measurement, the client considered multiple approaches. Please review the different approaches and answer the following question:

Which two options will yield a false result:

A. Option 2
B. Option 5
C. Option 4
D. Option 3
E. Option 1

Answer: B,E

Explanation:
The goal is to obtain a "Campaign Planned Clicks" value per Campaign, not accumulated by Media Buy keys.
Option 1 (SUM aggregation function) would sum all the "Campaign Planned Clicks" across Media Buy keys which would not yield the unique value per Campaign. Similarly, Option 5 (AVG aggregation function at Campaign Key level) would incorrectly average the values. Both options do not provide a way to return a singular "Campaign Planned Clicks" value for each Campaign.

NEW QUESTION # 48
......

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