SALESFORCE MARKETING-CLOUD-INTELLIGENCE PRINTABLE PDF, VALID TEST MARKETING-CLOUD-INTELLIGENCE VCE FREE

Salesforce Marketing-Cloud-Intelligence Printable PDF, Valid Test Marketing-Cloud-Intelligence Vce Free

Salesforce Marketing-Cloud-Intelligence Printable PDF, Valid Test Marketing-Cloud-Intelligence Vce Free

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
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
  • 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 6
  • 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 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
  • QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 9
  • Calculated Dimensions & Measurements: This section measures skills in using calculated objects, recognizing aggregation types, and employing these tools for tailored marketing analytics.
Topic 10
  • 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.

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q15-Q20):

NEW QUESTION # 15
Which two statements are correct regarding the Parent-Child configuration?

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

Answer: A,B

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 # 16
An implementation engineer has been asked to perform QA for a standard file ingestion, done by the client.
The source file that was ingested can be seen below:

The number of rows added to this data stream is 3. What could have led to this discrepancy?

  • A. All fields are mapped except for the Campaign Key
  • B. All fields are mapped except for the Media Buy Name.
  • C. All fields are mapped except for the Media Buy Key.
  • D. All fields are mapped except for the Creative Name

Answer: A

Explanation:
The source file shows data related to media buys, including a 'Media Buy Key', 'Media Buy Name', 'Campaign Key', and 'Site Key', among other fields. If only three rows were added, and the discrepancy is due to a missing field, it's likely that 'Campaign Key' is the field not mapped, because it is crucial for linking related records in the data stream. Without the 'Campaign Key', the system cannot associate the media buy data with specific campaigns, leading to a potential loss of data rows during ingestion.


NEW QUESTION # 17
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?

  • A.
  • B.
  • C.
  • D.

Answer: B

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 # 18
Your client would like to create a new harmonization field - Exam Topic.
The below table represents the harmonization logic from each source.

As can be seen from the table there are in fact two fields that hold a certain connection: Exam ID and Exam Topic. The connection indicates that where an Exam ID is found -a single Exam Topic value is associated with it.
The Client has a requirement to be able to view measurements from all data sources sliced by Exam Topic values as seen in the following example:

Which harmonization feature should an Implementation engineer use to meet the client's requirement?

  • A. Transformers
  • B. Custom Classification
  • C. Parent Chile
  • D. Fusion
  • E. Calculated dimensions

Answer: B

Explanation:
To meet the client's requirement of slicing measurements by 'Exam Topic' values, an Implementation Engineer should use Custom Classification. This feature allows different Exam IDs to be classified into their respective Exam Topics, ensuring that data from all sources can be accurately harmonized and analyzed based on these topics.


NEW QUESTION # 19
An implementation engineer is requested to integrate the following files:
File A:

File B:

The client would like to link the two files in order to view the two KPIS (Tasks Completed' and 'tasks Assignmed') alongside'Employee Name' and/or 'Squard'.
A Parent-Child configuration was set between the two.
Which two statements are correct?

  • A. The two files cannot be Joined as they hold different measurements
  • B. Any one of the files can potentially be set as the Parent data stream
  • C. The two files cannot be joined as they hold different dates
  • D. The two files were uploaded to a different Generic type
  • E. The join can be successful even if "empjd' isn't mapped and employee.name' is mapped to the same entity name in both data streams

Answer: B,E

Explanation:
In Marketing Cloud Intelligence, joining two files requires a common field to be mapped as the same entity. If "employee_name" is consistently mapped across both data streams, it can serve as the basis for the join, regardless of whether "employee_id" is mapped. The choice of which file serves as the Parent stream depends on the use case and the desired reporting structure, but technically, either could serve as the Parent.


NEW QUESTION # 20
......

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