Salesforce AP-215 Reliable Test Pdf | Exam AP-215 Sample

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Salesforce AP-215 Exam Syllabus Topics:

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

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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions (Q20-Q25):

NEW QUESTION # 20
An implementation 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?

Answer: D

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. Reference: Salesforce Marketing Cloud Intelligence documentation on creating custom measurements and calculated metrics.


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

Answer: C

Explanation:
For the client's data consisting of three data streams, setting Data Stream A as the Parent allows for inheriting attributes and hierarchies from it to the child data streams. This ensures consistency across the data streams, making it possible to analyze the data collectively, using the structure and attributes defined in the Parent data stream.


NEW QUESTION # 22
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 # 23
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
A pivot table was created to present the count of opportunities in each stage. The pivot table is filtered on Jan 7th - 11th. Which option reflects the stage(s) the Opportunity key 123AA01 is associated with?

Answer: D

Explanation:
Analyzing the Opportunity file with a filter set from January 7th to 11th, Opportunity Key '123AA01' appears under 'Interest' on January 6th and 8th, and under 'Registered' on January 10th. Therefore, during the specified date range, Opportunity Key '123AA01' is associated with both 'Interest' and 'Registered' stages. Salesforce Marketing Cloud Intelligence provides the capability to map and track opportunity stages over time, allowing for historical stage tracking and reporting. This answer aligns with the ability to use pivot tables to filter and display data by specific attributes and timeframes, as outlined in the Salesforce Marketing Cloud Intelligence documentation.


NEW QUESTION # 24
An implementation engineer is requested to extract the first three-letter segment of the Campaign Name values.
For example:
Campaign Name: AFD@Mulop-1290
Desired outcome: AFD
Other examples:

Which formula will return the desired values?

Answer: D

Explanation:
The EXTRACT function is used to split a string based on a delimiter and return the segment at the specified position. The campaign names are structured with the segment of interest followed by an '@' sign. Therefore, the formula needs to extract the segment before the '@'.
The correct formula is: EXTRACT(csv['campaign_name']; '@', 1). This will take the 'campaign_name' field, split it at the '@' sign, and return the first segment (position 1), which is the three-letter code that is required. The other options are incorrect because they do not properly specify the delimiter and the segment position in the way needed to achieve the desired outcome.


NEW QUESTION # 25
......

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