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Salesforce AP-215 Exam Syllabus Topics:

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

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Salesforce Marketing Cloud Intelligence Accredited Professional Sample Questions (Q46-Q51):

NEW QUESTION # 46
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?

Answer: A,D

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 # 47
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?

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). Reference: Salesforce Marketing Cloud Intelligence documentation on data integration, Parent-Child relationships, and QA procedures for data setup.


NEW QUESTION # 48
A client has provided you with sample files of their data from the following data sources:
1.Google Analytics
2.Salesforce Marketing Cloud
The link between these sources is on the following two fields:
Message Send Key
A portion of: web_site_source_key
Below is the logic the client would like to have implemented in Datorama:
For 'web site medium' values containing the word "email" (in all of its forms), the section after the "_" delimiter in 'web_site_source_key' is a 4 digit number, which matches the 'Message Send Key' values from the Salesforce Marketing Cloud file. Possible examples of this can be seen in the following table:
Google Analytics:

Salesforce Marketing Cloud:

The client's objective is to visualize the mutual key values alongside measurements from both files in a table.

In order to achieve this, what steps should be taken?

Answer: D

Explanation:
To create a linkage between Google Analytics and Salesforce Marketing Cloud data based on the "Message Send Key" and a portion of the "web_site_source_key," both values need to be harmonized into a common key. This is done by mapping the full Message Send Key from Salesforce Marketing Cloud and the extracted part of the web_site_source_key from Google Analytics to the same Custom Classification Key. This mapping will create a common identifier that can be used to combine the data from both sources for analysis and visualization.


NEW QUESTION # 49
An implementation engineer is requested to apply the following logic:

To apply the above logic, the engineer used only the Harmonization Center, without any mapping manipulations. What is the minimum amount of Patterns creating both 'Platform' and 'Line of Business'?"

Answer: C

Explanation:
To create both 'Platform' and 'Line of Business' fields using Patterns in the Harmonization Center without mapping manipulations, the engineer would need to create separate patterns for each data source mentioned. According to the provided images:
One pattern for LinkedIn Ads, to extract the 'Campaign Name' at position 4 for the Platform and 'Media Buy Name' at position 7 for Line of Business.
One pattern for AdRoll, to extract 'Media Buy Name' at position 3 for Platform and at position 2 for Line of Business.
One pattern for Google Analytics, which seems not required for the Platform but could apply if the Line of Business extraction is necessary, although it states N/A.
Hence, a minimum of 3 patterns would be necessary to create the fields required.


NEW QUESTION # 50
Which two statements are correct regarding LiteConnect?

Answer: A,B

Explanation:
LiteConnect is a feature in Salesforce Marketing Cloud Intelligence that allows users to bring external data into the platform quickly and easily. Here are the correct statements regarding LiteConnect:
A . LiteConnect allows for a quick setup by not requiring detailed identification of entities, keys, or categorization. Users can upload files without having to conform to the standard data model, which speeds up the process of data integration.
B . With LiteConnect, datasets are uploaded in their native format and do not conform to the standard data model of Marketing Cloud Intelligence. This means that the original structure of the dataset is maintained, and there is no need for extensive transformation or mapping upon the initial data import.
For C and D: While LiteConnect datasets might not conform to the standard data model initially, there are capabilities within Marketing Cloud Intelligence to further categorize and harmonize this data if needed. Therefore, C is not entirely correct, and D is incorrect because harmonization can indeed occur at a later step.


NEW QUESTION # 51
......

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