TOP SAMPLE MARKETING-CLOUD-INTELLIGENCE QUESTIONS - TRUSTABLE SALESFORCE MARKETING CLOUD INTELLIGENCE ACCREDITED PROFESSIONAL EXAM - MARKETING-CLOUD-INTELLIGENCE LATEST EXAM PREPARATION

TOP Sample Marketing-Cloud-Intelligence Questions - Trustable Salesforce Marketing Cloud Intelligence Accredited Professional Exam - Marketing-Cloud-Intelligence Latest Exam Preparation

TOP Sample Marketing-Cloud-Intelligence Questions - Trustable Salesforce Marketing Cloud Intelligence Accredited Professional Exam - Marketing-Cloud-Intelligence Latest Exam Preparation

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • Design Feasibility: This area evaluates the ability to identify valid and invalid solutions from solution design diagrams, ensuring effective and scalable platform designs.
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
  • QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.
Topic 5
  • 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 6
  • Data Model: In this domain, marketing professionals will explore data model entities, their relationships, and attributes within Marketing Cloud Intelligence.
Topic 7
  • 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 8
  • 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 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
  • 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 (Q27-Q32):

NEW QUESTION # 27
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 hasa 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. Calculated dimensions
  • B. Fusion
  • C. Custom Classification
  • D. Transformers
  • E. Parent Chile

Answer: C

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 # 28
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. 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
  • B. 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.
  • C. 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.
  • D. 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

Answer: A,D

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 # 29
A client created a new KPI: CPS (Cost per Sign-up).
The new KIP is mapped within the data stream mapping, and is populated with the following logic: (Media Cost) / Sign-ups) As can be seen in the table below, CPS was created twice and was set with two different aggregations:

From looking at the table, what are the aggregation settings for each one of the newly created KPIs?

  • A.
  • B.
  • C.
  • D.

Answer: B

Explanation:
The KPI CPS (Cost per Sign-up) would be calculated by dividing the 'Media Cost' by 'Sign-ups'. The table indicates that CPS is set with two different aggregations. In option C, CPS #1 is set to 'AUTO', which allows the system to decide the best aggregation method based on the context. CPS #2 is set to 'SUM', which indicates that the individual costs per sign-up are summed up across multiple records to provide a total cost per sign-up.


NEW QUESTION # 30
A client would like to integrate the following two sources:
Google Campaign Manager:

IAS:

After configuring a Parent-Child relationship between the files, which query should an implementation engineer run in order to QA the setup?

  • A. Media Buy Type, Media Buy Name, Impressions, Analyzed Impressions
  • B. Media Buy Type, Analyzed Impressions
  • C. Creative Name, Impressions, Analyzed Impressions
  • D. Media Buy Name, Impressions

Answer: A

Explanation:
To QA the Parent-Child relationship setup between Google Campaign Manager and IAS data sources, it is essential to query fields that are common to both sources and that are relevant to the relationship. 'Media Buy Type' and 'Media Buy Name' are common identifiers between the two datasets. 'Impressions' from the Google Campaign Manager and 'Analyzed Impressions' from the IAS data are the metrics that should be compared to ensure they match or correlate as expected due to the Parent-Child relationship. The QA process involves checking that the data is correctly aligned and that the metrics from the parent source (Google Campaign Manager) are properly related to the metrics from the child source (IAS). References: Salesforce Marketing Cloud Intelligence documentation on data integration, Parent-Child relationships, and QA procedures for data setup.


NEW QUESTION # 31
Which Marketing Cloud Intelligence field is considered an attribute and not a "variable"?

  • A. Geo Location
  • B. Device Browser
  • C. Device Category
  • D. Campaign Category

Answer: C


NEW QUESTION # 32
......

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