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Salesforce AP-215 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Visualization and Dashboards	- Filters and Drill-Downs 1. Global and local filters 2. Drill-down configuration - Calculated Measurements 1. Formulas and functions 2. Creating custom calculations - Dashboard Design 1. KPI widgets and chart types 2. Building dashboards
Topic 2: 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 3: 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
Topic 4: Data Harmonization and Data Model	- Dimensions and Measures 1. Calculated measurements 2. Creating and managing measures (KPIs) 3. Creating and managing dimensions - Data Classification 1. Attribute classification 2. Hierarchy management - Parent-Child Data Streams 1. Linking data streams 2. Override Media Buy Hierarchies 3. Data Update Permissions
Topic 5: 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 (Q40-Q45):

NEW QUESTION # 40
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?

A. Within both files, map the desired value to Custom Classification Key as follows Salesforce Marketing Cloud: map entire Message Key to Custom Classification Key.
Google Analytics: map the extraction logic to Custom Classification Key.
B. Create a Web Analytics Site Source custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
C. Create a Web Analytics Site custom attribute and populate it with the extraction logic. Create a Data Fusion between the newly created attribute and the Message Send Key.
D. Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.

Answer: A

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 # 41
Which two statements are correct regarding LiteConnect?

A. It does not require any identification of entities, keys or any other categorization.
B. Data coming from LiteConnect cannot be harmonized with the rest of the workspace data via the harmonization center at a later step.
C. All of the dimensions mapped within a LiteConnect data stream are considered overarching entities.
D. The dataset does not conform to the standard data model

Answer: A,D

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 # 42
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?

A. Two separate patterns (filtered by Linkedin or AdRoll sources)
Within Google Analytics' mapping A formula that reflects the logic above will be populated within a Web Analytics Site custom attribute Another pattern to be created for the newly Web Analytics Site custom attribute (filtered by Google Analytics source).
A total of 3 patterns.
B. Two separate patterns (filtered by Linkedin or AdRoll sources)
Within Google Analytics' mapping: A formula that reflects the logic above will be populated within a Campaign custom attribute.
Another pattern to be created for the newly campaign attribute (filtered by Google Analytics source).
A total of 3 patterns
C. Two separate patterns (filtered by Linkedin or AdRoll sources).
Another single pattern for Campaign Name (filtered by Google Analytics source).
A total of 3 patterns.
D. Two separate patterns (filtered by Linkedln or AdRoll sources).
Another single pattern for Web Analytics Site Source (filtered by Google Analytics source), extracting all three positions A total of 3 patterns.

Answer: B

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 # 43
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activity analysis. Below are details regarding the different data sources and the number of data streams required for each source.

When harmonizing the Objective field from within the data stream mapping, which advantage is gained?

A. Performance (Performance when loading a dashboard page)
B. Ease of Setup
C. Ease of Maintenance
D. Scalability

Answer: C

Explanation:
By harmonizing the Objective field within data stream mapping, an organization can benefit from:
Ease of Maintenance: Harmonization allows for consistent naming conventions across different data sources and streams. This means when business logic or naming conventions change, updates can be made in one place and consistently applied across all data streams. It also reduces the complexity of managing multiple streams and ensures data consistency, which is vital for accurate reporting and analysis.

NEW QUESTION # 44
What Is a disadvantage of using a Vlookup formula?

A. Could extend processing time of data streams.
B. It cannot be used more than once from the same data stream.
C. Can return values only from the same data stream type
D. It allows classifying data only on a basis of mutual entity keys.

Answer: A

Explanation:
The use of VLOOKUP formulas can increase the processing time of data streams because it requires a lookup operation for each row in the data set. When large volumes of data are involved, or when multiple VLOOKUPs are used, this can significantly impact processing time due to the complexity and computational requirements of matching and retrieving the data.

NEW QUESTION # 45
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