NEW SALESFORCE MARKETING-CLOUD-INTELLIGENCE REAL EXAM, PASS4SURE MARKETING-CLOUD-INTELLIGENCE STUDY MATERIALS

New Salesforce Marketing-Cloud-Intelligence Real Exam, Pass4sure Marketing-Cloud-Intelligence Study Materials

New Salesforce Marketing-Cloud-Intelligence Real Exam, Pass4sure Marketing-Cloud-Intelligence Study Materials

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>> New Salesforce Marketing-Cloud-Intelligence Real Exam <<

Free PDF Marvelous Salesforce - Marketing-Cloud-Intelligence - New Marketing Cloud Intelligence Accredited Professional Exam Real Exam

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Salesforce Marketing-Cloud-Intelligence Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 4
  • 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 5
  • 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 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
  • 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
  • QA Ability: This section focuses on common QA steps for various scenarios, enabling Salesforce marketing professionals to ensure data quality and platform performance.

Salesforce Marketing Cloud Intelligence Accredited Professional Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
Animplementation engineer has been provided with 4 different source files: 03m 48s
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 by
File structure/headers:

  • A.
  • B.
  • C.
  • D.

Answer: B

Explanation:
In Salesforce Marketing Cloud Intelligence, connections between source files and classification files are established through common keys that link data records. For this scenario:
* The "1st Party Creative Classification" file has a "Creative ID" field which corresponds to the "Creative Key" in the "Twitter Ads" data. This link enables enrichment of Twitter Ads data with creative classification details.
* The "1st Party Placement Classification" file will contain a "Placement ID" that connects to a corresponding field in the "Twitter Ads" data, enabling the enrichment of placement classification details.
Option A appears to accurately depict this setup where data streams for "Creative Classification" and
"Placement Classification" are connected to the "Twitter Ads" data stream using the "Creative ID" and
"Placement ID", respectively. This structure allows for the enhancement of the main Twitter Ads data with additional classification information.


NEW QUESTION # 25
Animplementation engineer has been provided with the below dataset:

*Note: CPC = Cost per Click
Formula: Cost / Clicks
Which action should an engineer take to successfully integrate CPC?

  • A. Populate the logic within a custom measurement. Set Aggregation to AVG.
  • B. Populate the logic within a custom measurement. Set Aggregation to SUM.
  • C. Populate the logic within a custom measurement. No need to change Aggregation.
  • D. Unmap it, as Datorama will calculate it automatically.

Answer: C

Explanation:
CPC (Cost per Click) is a calculated metric that should be created using a custom measurement based on the formula provided (Cost / Clicks). This calculation does not require a change in the aggregation setting because it is derived from other base metrics that are already aggregated appropriately. In Salesforce Marketing Cloud Intelligence, custom measurements are used to create new metrics from existing data points, and the system will use the underlying data's aggregation to perform the calculation. References: Salesforce Marketing Cloud Intelligence documentation on creating custom measurements and calculated metrics.


NEW QUESTION # 26
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
"Opportunity Count" - Generic Custom Metric
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on January (entire month). What is the number of opportunities in the Interest stage?

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: B

Explanation:
Based on the Opportunity file, the Opportunity Stage of 'Interest' occurs 3 times across unique Opportunity Keys. Since the pivot table is filtered to present the entire month of January and the Opportunity Stage 'Interest' is listed three times with different Opportunity Keys, the count of opportunities in the 'Interest' stage would be 3.


NEW QUESTION # 27
Source 3:

Via the harmonization Center, the Client has created Patterns and applied a classification rule using source 2.
While performing QA, you have spotted that the final value of clicks for Product Group Ais 10, where it should've been i5.

How can an implementation engineer fix this discrepancy?

  • A. Leave the "Case Sensitive" checkbox in the data classification unchecked
  • B. Toggle the 'Structure Compliant' OFF.
  • C. Uncheck the "Case Sensitive" checkbox in the data classification
  • D. Upload both source 1 and 3 to the same data stream type in order to be able to generate Patterns from them.

Answer: C

Explanation:
Case Sensitivity Issue:
The discrepancy in the "Clicks" value for Product Group A (10 instead of 15) likely arises from a mismatch caused by case sensitivity in the classification rules. If some data entries use different capitalization (e.g., "Product Group A" vs. "product group a"), the system might treat them as distinct entries, leading to incorrect aggregations.
Solution:
By unchecking the "Case Sensitive" checkbox, the harmonization process will treat entries with different capitalization as the same value. This ensures consistent classification and resolves discrepancies in aggregated metrics like "Clicks."


NEW QUESTION # 28
Which two statements are correct regarding the Parent-Child configuration?

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

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 # 29
......

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