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Marketing-Cloud-Intelligence Certification Training - Test Marketing-Cloud-Intelligence Guide Online

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

Topic
Details

Topic 1

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

Topic 2

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 3

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 4

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 5

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

Topic 6

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 7

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

Topic 8

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 9

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 10

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 11

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 12

Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.

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Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q63-Q68):

NEW QUESTION # 63
Which two statements are correct regarding the Parent-Child configuration?

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

Answer: A,C

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 # 64
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activityanalysis. Below are details regarding the different data sources and the number of data streams required for each source.

What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?

A. Use of code
B. Ease of Maintenance
C. Processing (processing time when loading relevant data streams)
D. Scalability
E. Performance (Performance when loading a dashboard page)

Answer: B,D,E

Explanation:
Patterns & Data Classification in Marketing Cloud Intelligence offer several advantages. These include:
* Ease of Maintenance (A):Patterns allow for the standardization of data harmonization processes. Once set up, they can be easily maintained and adjusted as needed, without having to manipulate each data stream individually.
* Performance (B):By using patterns, data is classified and standardized at ingestion, which can improve the performance of dashboard page loading because the system does not need to perform complex, on-the-fly calculations or transformations.
* Scalability (D):Patterns can be applied across multiple data streams consistently, allowing them to scale with the data. This means that as the amount of data grows or as new data sources are added, the same patterns can be reused, ensuring that the data remains harmonized.

NEW QUESTION # 65
Which three entities and/or functions can be used in an expression when building a calculated dimension?

A. The EXTRACT function
B. Mapped measurements
C. Calculated dimensions
D. Mapped dimensions
E. The VLOOKUP function

Answer: A,B,D

Explanation:
Calculated dimensions (D) and the VLOOKUP function (A) are not typically used within the expression for a calculated dimension. Calculated dimensions are usually an output, not an input, and VLOOKUP is a function typically used to enrich or connect data, not within the definition of a calculated dimension itself.
Explanation:
In the context of Marketing Cloud Intelligence, when building a calculated dimension, you can typically use:
B). Mapped dimensions: These are dimensions that have been brought into Marketing Cloud Intelligence through the data integration process and have been mapped to a known schema or model.
C). The EXTRACT function: This function can be used to dynamically create dimensions by extracting values from a mapped dimension or measurement.
E). Mapped measurements: Similar to mapped dimensions, these are quantitative data points that have been integrated into the platform and can be referenced in calculations.

NEW QUESTION # 66
Which two statements are correct regarding LiteConnect?

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

Answer: B,C

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 # 67
Your client is interested in ingesting the below file:

The client decided to upload the file to a new generic data stream type and map 'Date' to 'Day' and 'Number of Topics' to a generic custom metric.
In regards to the fields 'Meeting Code' and 'Meeting Name', your client is debating several options.
Which two options would you recommend in order to avoid data loss?

A. 'Meeting Code' will be mapped to 'Main Generic Entity custom attribute'.
'Meeting Name' will be mapped to 'Generic Entity Key'
B. Concatenation of both 'Meeting Code' and 'Meeting Name' will be mapped to 'Main Generic Entity Key'.
'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'.
C. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Generic Entity 2 Key'.
D. 'Meeting Code' will be mapped to 'Main Generic Entity Attribute 1'.
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.
E. 'Meeting Code' will be mapped to 'Main Generic Entity Key'.
'Meeting Name' will be mapped to 'Main Generic Entity custom attribute'.

Answer: B,E

Explanation:
'Meeting Name' will be mapped to 'Main Generic Entity Attribute 2'.
Explanation:
To avoid data loss and ensure each meeting is uniquely identified and its details are preserved, two mappings are recommended:
Option A:
'Meeting Code' should be mapped to the 'Main Generic Entity Key' to uniquely identify each meeting.
'Meeting Name' should be mapped to a 'Main Generic Entity custom attribute' to store additional information about the meeting.
Option E:
Concatenation of 'Meeting Code' and 'Meeting Name' should be mapped to 'Main Generic Entity Key'. This ensures a unique identifier for each meeting is created combining both pieces of information, preventing any mix-ups between meetings with similar codes or names.
Additionally, mapping 'Meeting Code' and 'Meeting Name' to their respective 'Main Generic Entity Attribute' fields will allow for more detailed filtering and reporting capabilities within Marketing Cloud Intelligence.

NEW QUESTION # 68
......

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Ted Ward Ted Ward

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