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Salesforce AP-215 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Visualization and Dashboards- Calculated Measurements
  • 1. Formulas and functions
  • 2. Creating custom calculations
- Dashboard Design
  • 1. Building dashboards
  • 2. KPI widgets and chart types
- Filters and Drill-Downs
  • 1. Global and local filters
  • 2. Drill-down configuration
Topic 2: 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
Topic 3: Data Integration and Configuration- Data Ingestion
  • 1. File upload and API data sources
  • 2. Scheduling and refresh settings
- Data Mapping
  • 1. Data model configuration
  • 2. Mapping fields from source files
- Data Stream Types
  • 1. Configuring data source properties
  • 2. Understanding different data stream types
Topic 4: Data Harmonization and Data Model- Data Classification
  • 1. Hierarchy management
  • 2. Attribute classification
- Dimensions and Measures
  • 1. Creating and managing measures (KPIs)
  • 2. Calculated measurements
  • 3. Creating and managing dimensions
- Parent-Child Data Streams
  • 1. Override Media Buy Hierarchies
  • 2. Linking data streams
  • 3. Data Update Permissions
Topic 5: Marketing Intelligence Platform Fundamentals- Administration and Security
  • 1. User management and permissions
  • 2. Workspace and account settings
- Platform Overview
  • 1. Key features and capabilities
  • 2. Marketing Cloud Intelligence (formerly Datorama) overview

>> Reliable AP-215 Exam Questions <<

Free PDF Quiz 2026 Salesforce AP-215: Valid Reliable Marketing Cloud Intelligence Accredited Professional Exam Questions

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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions (Q12-Q17):

NEW QUESTION # 12
An implementation engineer is requested to create the harmonization field - Magician This field should come from multiple Twitter Ads data streams, and should follow the below logic:

Using the Harmonization Center, the engineer created a single Pattern for Campaign Name. What other action should the engineer take to meet the requirements?

Answer: D

Explanation:
For the field 'Magician', the engineer is required to follow a logic that extracts a value from 'Campaign Name' and checks against a validation list for specific values ('Messi' or 'Ronaldo'). If those values are not found, it should instead extract from 'Media Buy Name'. To accomplish this, the engineer should:
Use the created Pattern for 'Campaign Name'.
Create a second Pattern for 'Media Buy Name' to capture the fallback values.
Apply two Classification Rules to the Harmonized Dimension: one for the value 'Messi' and another for 'Ronaldo'. This is to check the extracted 'Campaign Name' against these specific values.
These steps ensure that the 'Magician' field will be populated with the correct values from the respective data streams following the specified logic.


NEW QUESTION # 13
A client Ingested the following We into Marketing Cloud Intelligence:

The mapping of the above file can be seen below:
Date - Day
Media Buy Key - Media Buy Key
Campaign Name - Campaign Name
Campaign Group -. Campaign Custom Attribute 01
Clicks -> Clicks
Media Cost -> Media Cost
Campaign Planned Clicks -> Delivery Custom Metric 01
The client would like to have a "Campaign Planned Clicks" measurement.
This measurement should return the "Campaign Planned Clicks" value per Campaign, for example:
For Campaign Name 'Campaign AAA", the "Campaign Planned Clicks" should be 2000, rather than 6000 (the total sum by the number of Media Buy keys).
In order to create this measurement, the client considered multiple approaches. Please review the different approaches and answer the following question:

Which two options will yield a false result:

Answer: C,E

Explanation:
The goal is to obtain a "Campaign Planned Clicks" value per Campaign, not accumulated by Media Buy keys. Option 1 (SUM aggregation function) would sum all the "Campaign Planned Clicks" across Media Buy keys which would not yield the unique value per Campaign. Similarly, Option 5 (AVG aggregation function at Campaign Key level) would incorrectly average the values. Both options do not provide a way to return a singular "Campaign Planned Clicks" value for each Campaign.


NEW QUESTION # 14
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?

Answer: A

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 # 15
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?

Answer: A,C

Explanation:
For performance issues when loading a dashboard using CRM data stream type:
Pacing can create performance issues because daily rows for every lead and opportunity key can result in a very large number of rows, increasing load times.
Having only calculated measurements means there are no direct, mappable values to query against, which can increase the computational load and affect performance.


NEW QUESTION # 16
An Implementation engineer is requested to create a new harmonization field 'Offer' and apply the following logic:

The implementation engineer to use the Harmonization Center. Which of the below actions can help implement the new dimension 'Offer?

Answer: C

Explanation:
To implement the new harmonization field 'Offer', the implementation engineer would create two separate harmonization patterns for LinkedIn and AdRoll sources, extracting the 'Campaign Name' using the specified delimiter and position. Then, within Google Analytics' mapping, a custom attribute for the 'Campaign' would be created to apply the formula logic based on the source. This allows for the harmonization of campaign data across different platforms, ensuring consistency in the reporting and analysis within Marketing Cloud Intelligence. The total patterns required would be three, one for each data source involved.


NEW QUESTION # 17
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