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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic	Details
Topic 1	QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 2	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 3	Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 4	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 5	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 6	Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.
Topic 7	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 8	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 9	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 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	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 12	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 (Q29-Q34):

NEW QUESTION # 29
A client provides the following two data streams:
Data Stream 1:

Question-
The client would like to use a VLOOKUP formula to calculate the Cost per Campaign Advertiser on January
1st 2020. Which mapping options should the client apply to obtain the expected result?

Answer: B

Explanation:
To calculate Cost per Campaign Advertiser using a VLOOKUP formula, the client needs to look up the 'Cost' from Data Stream 2 based on a matching 'Media Buy Name' in Data Stream 1. Option A shows that 'Media Buy Name' is the lookup value, which is correct. The 'Campaign Advertiser' is then linked to the 'Cost' from Data Stream 2 through the VLOOKUP formula applied to the 'Media Buy Custom Attribute 01' in Data Stream 2. This setup will correctly associate the cost with the campaign advertiser.

NEW QUESTION # 30
Animplementation 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. Calculated Dimensions
B. Mapping formula
C. Patterns
D. Data Fusion
E. Vlookup 0

Answer: A,B,C

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 withindata 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 # 31
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?

A. The data is stored at the workspace level.
B. When a data stream type ''CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
C. No mappable measurements - all measurements are calculated
D. Pacing - daily rows are being created for every lead and opportunity keys

Answer: C,D

Explanation:
For performance issues when loading a dashboard using CRM data stream type:
* Pacing can create performance issues because daily rows for every lead and opportunity key can result in a very large number of rows, increasing load times.
* Having only calculated measurements means there are no direct, mappable values to query against, which can increase the computational load and affect performance.

NEW QUESTION # 32
Which two statements are correct regarding LiteConnect?

A. Data coming from LiteConnect cannot be harmonized with the rest of the workspace data via the harmonization center at a later step.
B. The dataset does not conform to the standard data model
C. All of the dimensions mapped within a LiteConnect data stream are considered overarching entities.
D. It does not require any identification of entities, keys or any other categorization.

Answer: B,D

Explanation:
LiteConnect is a feature in Salesforce Marketing Cloud Intelligence that allows users to bring external data into the platform quickly and easily. Here are the correct statements regarding LiteConnect:
* A.LiteConnect allows for a quick setup by not requiring detailed identification of entities, keys, or categorization. Users can upload files without having to conform to the standard data model, which speeds up the process of data integration.
* B.With LiteConnect, datasets are uploaded in their native format and do not conform to the standard data model of Marketing Cloud Intelligence. This means that the original structure of the dataset is maintained, and there is no need for extensive transformation or mapping upon the initial data import.
For C and D: While LiteConnect datasets might not conform to the standard data model initially, there are capabilities within Marketing Cloud Intelligence to further categorize and harmonize this data if needed.
Therefore, C is not entirely correct, and D is incorrect because harmonization can indeed occur at a later step.

NEW QUESTION # 33
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.

Which three advantages does a client gain from using Calculated Dimensions as the harmonization method for creating the Objective field?

A. Data model restrictions - Calculated Dimensions do not need to adhere to Marketing Cloud Intelligence's data model
B. Processing - creation of Calculated Dimensions will ease the processing time of the data streams it relates to
C. Performance (Performance when loading a dashboard page) should be optimized as the values of calculated dimensions are stored within the database.
D. Ease of Maintenance - the logic is written and populated in one centralized place
E. Scalability - future data streams that will follow similar logic will be automatically harmonized.

Answer: C,D,E

Explanation:
Scalability: Using Calculated Dimensions allows the client to apply the same harmonization logic to future data streams, ensuring consistency and reducing the need for individual adjustments.
Ease of Maintenance: With the logic centralized in Calculated Dimensions, any adjustments or updates are applied in one place, simplifying ongoing management.
Performance: Calculated Dimensions can improve dashboard performance because their values are pre-computed and stored, reducing the need for real-time calculations when loading dashboards.

NEW QUESTION # 34
......

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Tony Gray Tony Gray

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Marketing-Cloud-Intelligence New Learning Materials & Reliable Marketing-Cloud-Intelligence Test Dumps

Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Reliable Marketing-Cloud-Intelligence Test Dumps | New Marketing-Cloud-Intelligence Test Sims

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q29-Q34):

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Tony Gray Tony Gray

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Marketing-Cloud-Intelligence New Learning Materials & Reliable Marketing-Cloud-Intelligence Test Dumps

Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Reliable Marketing-Cloud-Intelligence Test Dumps | New Marketing-Cloud-Intelligence Test Sims

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q29-Q34):