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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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

Topic 4

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 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

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

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.

Topic 8

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

Topic 9

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 10

Overarching Entities: Salesforce marketing professionals will deepen their understanding of overarching entities, their use cases, and application, crucial for strategic data organization and analysis.

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

NEW QUESTION # 12
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.

When harmonizing the Objective field from within the data stream mapping, which advantage is gained?

A. Performance (Performance when loading a dashboard page)
B. Scalability
C. Ease of Maintenance
D. Ease of Setup

Answer: C

Explanation:
By harmonizing the Objective field within data stream mapping, an organization can benefit from:
* Ease of Maintenance: Harmonization allows for consistent naming conventions across different data sources and streams. This means when business logic or naming conventions change, updates can be made in one place and consistently applied across all data streams. It also reduces the complexity of managing multiple streams and ensures data consistency, which is vital for accurate reporting and analysis.

NEW QUESTION # 13
A client has provided you with sample files of their data from the following data sources:
1.Google Analytics
2.Salesforce Marketing Cloud
The link between these sources is on the following two fields:
Message Send Key
A portion of: web_site_source_key
Below is the logic the client would like to have implemented in Datorama:
For 'web site medium' values containing the word "email" (in all of its forms), the section after the "_" delimiter in 'web_site_source_key' is a 4 digit number, which matches the 'Message Send Key' values from the Salesforce Marketing Cloud file. Possible examples of this can be seen in the following table:
Google Analytics:

Salesforce Marketing Cloud:

The client's objective is to visualize the mutual key values alongside measurements from both files in a table.

In order to achieve this, what steps should be taken?

A. Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.
B. Create a Web Analytics Site custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
C. Create a Web Analytics Site Source custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
D. Within both files, map the desired value to Custom Classification Key as follows Salesforce Marketing Cloud: map entire Message Key to Custom Classification Key.
Google Analytics: map the extraction logic to Custom Classification Key.

Answer: D

Explanation:
To create a linkage between Google Analytics and Salesforce Marketing Cloud data based on the "Message Send Key" and a portion of the "web_site_source_key," both values need to be harmonized into a common key. This is done by mapping the full Message Send Key from Salesforce Marketing Cloud and the extracted part of the web_site_source_key from Google Analytics to the same Custom Classification Key. This mapping will create a common identifier that can be used to combine the data from both sources for analysis and visualization.

NEW QUESTION # 14
Which two statements are correct regarding the Parent-Child configuration?

A. A Parent-Child cannot be configured between an Ads data stream type and a Conversion Tag one.
B. Parent-Child allows sharing both dimensions and measurements
C. Parent-Child links different tables based on shared key values
D. Parent-Child configurations can cause performances issues

Answer: C,D

Explanation:
Parent-Child configurations in Marketing Cloud Intelligence are used to link different data tables based on shared key values, allowing for the relational organization of data across variousstreams. While this setup enhances data analysis and reporting by maintaining logical relationships between parent and child tables, it can also introduce performance issues. The complexity increases with the number of relationships and the volume of data, potentially slowing down query processing and data manipulation. Additionally, Parent-Child configurations facilitate the sharing of dimensions and measurements across linked tables, enhancing the data's usability without duplicating it.

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

Answer: B

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 # 16
After uploading a standard file into Marketing Cloud intelligence via totalConnect, you noticed that the number of rows uploaded (to the specific data stream) is NOT equal to the number of rows present in the source file. What are two resource that may cause thisgap?

A. The file does not contain any measurements (dimension only)
B. Main entity is not mapped
C. The source file does not contain the mediaBuy entity
D. All mapped Measurements for a given row have values equal to zero

Answer: B,D

Explanation:
In Marketing Cloud Intelligence, discrepancies between the number of rows uploaded and the number of rows present in the source file can be caused by several factors. If all mapped measurements for a row are zero, that row may be excluded from the upload, as it does not contribute to the analytics. Additionally, if the main entity, which acts as the primary identifier for records, is not mapped, the system cannot correctly ingest the data as it lacks the necessary reference to organize and store the information.

NEW QUESTION # 17
......

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