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Salesforce AP-215 Exam Syllabus Topics:

SectionObjectives
Data Visualization and Dashboards- Dashboard Design
  • 1. Building dashboards
  • 2. KPI widgets and chart types
- Calculated Measurements
  • 1. Creating custom calculations
  • 2. Formulas and functions
- Filters and Drill-Downs
  • 1. Drill-down configuration
  • 2. Global and local filters
Marketing Intelligence Platform Fundamentals- Administration and Security
  • 1. User management and permissions
  • 2. Workspace and account settings
- Platform Overview
  • 1. Marketing Cloud Intelligence (formerly Datorama) overview
  • 2. Key features and capabilities
Reports and Activation- Report Types
  • 1. Report scheduling
  • 2. Standard and custom reports
- Data Export
  • 1. Exporting data and insights
  • 2. Integration with external tools
Data Integration and Configuration- Data Mapping
  • 1. Mapping fields from source files
  • 2. Data model configuration
- Data Ingestion
  • 1. Scheduling and refresh settings
  • 2. File upload and API data sources
- Data Stream Types
  • 1. Understanding different data stream types
  • 2. Configuring data source properties
Data Harmonization and Data Model- Data Classification
  • 1. Attribute classification
  • 2. Hierarchy management
- Dimensions and Measures
  • 1. Creating and managing dimensions
  • 2. Creating and managing measures (KPIs)
  • 3. Calculated measurements
- Parent-Child Data Streams
  • 1. Linking data streams
  • 2. Data Update Permissions
  • 3. Override Media Buy Hierarchies

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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions (Q18-Q23):

NEW QUESTION # 18
A client provides the following two data streams:
Data Stream 1:

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 # 19
Which two statements are correct regarding the Parent-Child configuration?

Answer: B,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 various streams. 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 # 20
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" - Main Generic Entity Attribute
"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 Jan 11th. What is the number of opportunities in the Interest stage?

Answer: D

Explanation:
Since the pivot table is filtered on January 11th and the provided Opportunity file does not show any records dated January 11th, there are zero opportunities in the Interest stage for that date. Salesforce Marketing Cloud Intelligence allows users to create pivot tables and filter data based on specific criteria, such as dates. In this case, the filter would exclude all rows that do not match the specified date, resulting in a count of zero for the Interest stage. This would apply to any stage since there are no records for January 11th. Reference can be made to Salesforce Marketing Cloud Intelligence documentation on filtering and pivot tables.


NEW QUESTION # 21
A client's data consists of three data streams as follows:
Data Stream A:

* The data streams should be linked together through a parent-child relationship.
* Out of the three data streams, Data Stream C is considered the source of truth for both the dimensions and measurements.
How should the "Override Media Buy Hierarchies" checkbox be set in order to meet the client's requirements?

Answer: C

Explanation:
If Data Stream C is the source of truth, the "Override Media Buy Hierarchies" checkbox should be checked for Data Stream C.
This means that the hierarchy defined within Data Stream C will take precedence over any other media buy hierarchies present in Data Streams A or B. By doing so, it enforces that the hierarchy from the source of truth (Data Stream C) is used throughout the dataset, maintaining the integrity of the hierarchical relationships as defined by the most reliable data source.


NEW QUESTION # 22
Which three statements describe Overarching Entities? 03m 23s

Answer: A,C,D

Explanation:
Overarching Entities in Salesforce Marketing Cloud Intelligence are designed to provide a high level of data organization that spans across multiple data streams. The key points about Overarching Entities are:
B . Relationship Types: Overarching entities can have either a Many-to-Many or One-to-Many relationship with the main entity, which allows for flexible data modeling and relationship definitions based on the nature of the data and how it should be analyzed and reported.
C . Acting as Main Entity: They can serve as a main entity in certain situations, enabling a shift in perspective for data analysis. This can be particularly useful when there is a need to view data from a different dimension that is more aligned with business requirements.
E . Storage Level: The values of these entities are not tied to any single data stream but are maintained at a workspace level, ensuring that they can be applied consistently across different datasets, which is critical for maintaining data integrity and ensuring that classifications are applied uniformly.


NEW QUESTION # 23
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