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Marketing-Cloud-Intelligence Practice Questions

Question # 1
The following file was uploaded into Marketing Cloud Intelligence as a Generic Data Stream type:



The mapping is as follows:
Day — Day
web_site_key —> Main Generic Entity Key web_site_name —> Main Generic Entity Name Web_site_source —> Main Generic Entity Attribute 01 Page Views — Generic Metric 1
How many rows will be stored in Marketing Cloud Intelligence after the above file is ingested?
A. 1
B. 0
C. 3
D. 4


D. 4

Explanation: With the uploaded file mapped as a Generic Data Stream type, the unique identifier for a row is the combination of 'Day', 'web_site_key', 'web_site_name', and'Web_site_source'. As 'Day' is mapped to 'Day', 'web_site_key' to 'Main Generic Entity Key', 'web_site_name' to 'Main Generic Entity Name', and 'Web_site_source' to 'Main Generic Entity Attribute 01', each unique combination of these fields will constitute a separate row.
The provided file has 4 unique combinations of 'Day', 'web_site_key', 'web_site_name', and 'Web_site_source', as each line has a unique 'web_site_key' and 'web_site_name'.
Consequently, Marketing Cloud Intelligence will store 4 rows, one for each unique combination.

Question # 2
A client has integrated data from Facebook Ads. Twitter ads, and Google ads in marketing Cloud intelligence. For each data source, the source, the data follows a naming convensions as …
Facebook Ads Naming Convention - Campaign Name:
CampID_CampName#Market_Object#object#targetAge_TargetGender Twitter Ads Naming Convention- Media Buy Name MarketTargeAgeObjectiveOrderID
Google ads Naming Convention-Media Buy Name: Buying_type_Market_Objective
The client wants to harmonize their data on the common fields between these two platforms (i.e. Market and Objective) using the Harmonization Center. Given the above information, which statement is correct regarding the ability to implement this request?
wet Me - Given the above information, which statement i 's Correct regarding the ability to implement this request?
A. The clientWi-Fibe able to harmonize only Google Ads and Twitter Ads, as Facebook Ads naming convention contains mufti delimiters.
B. it is not possible to do this, as the naming conventions are different
C. This is not possible as the naming conventions are in different fields (Campaign Name and Placement Name)
D. The client will be able to do this and it will require building three patterns.


D. The client will be able to do this and it will require building three patterns.

Explanation: Despite the different naming conventions, harmonization is possible using patterns in the Harmonization Center. By extracting the 'Market' and 'Objective' components from the naming conventions of each platform, three separate patterns would be created to map these common fields consistently across the data from Facebook Ads, Twitter Ads, and Google Ads.

Question # 3
What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
A. When a data stream type ''CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
B. Pacing - daily rows are being created for every lead and opportunity keys
C. No mappable measurements - all measurements are calculated
D. The data is stored at the workspace level.


B. Pacing - daily rows are being created for every lead and opportunity keys
C. No mappable measurements - all measurements are calculated

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.

Question # 4
An implementation engineer has been asked by a client for assistance with the following problem: The below dataset was ingested:



However, when performing QA and querying a pivot table with Campaign Category and Clicks, the value for Type’ is 4.
What could be the reason for this discrepancy?
A. The measurement ‘Clicks’ is set as a percentage.
B. A mapping formula was populated, indicating not to bring Type! values.
C. The aggregation function is set as AVG
D. The aggregation function is set as LIFETIME


C. The aggregation function is set as AVG

Explanation: The discrepancy of 'Clicks' being reported as 4 for 'Type1' when the sum of clicks in the dataset for 'Type1' is 8 (2 on 02/02/2021 and 6 on 03/02/2021) suggests that the aggregation function used in the pivot table is set to average (AVG) rather than sum. Salesforce Marketing Cloud Intelligence allows setting different aggregation functions for metrics, and setting it to average would result in such a discrepancy when more than one entry for the same type exists. References: Salesforce Marketing Cloud Intelligence documentation on custom measurements and data aggregations explains how to set and understand different aggregation functions.

Question # 5
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.

Assuming the data was ingested properly and the Parent Child was created correctly according to the client's requirements, what is the total Impressions value for Campaign Key ‘CK_3’?
A. N-A
B. 100
C. 300
D. 150


B. 100

Explanation: Assuming that Data Stream A is set correctly with parent-child relationships: To find the total impressions for Campaign Key 'CK_3', you would look in Data Stream A, since it contains the 'Impressions' metric. As per the provided data, Campaign Key ‘CK_3’ has 100 impressions.

Question # 6
A client's data consists of three data streams as follows:



* 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.

Which data stream should be set as a parent?
A. Data Stream A
B. Data Stream C
C. Any of the data streams can technically be the parent
D. Data Stream B


B. Data Stream C

Explanation: Since Data Stream C is considered the source of truth for both dimensions and measurements, it should be set as the parent data stream. This is because the parent data stream is used as the primary source for hierarchical and attribute data within a parent-child relationship setup. As the source of truth, Data Stream C will provide the foundational data upon which the other streams can be aligned and will ensure consistency and accuracy across the linked data.

Question # 7
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.



Which three advantages does a client gain from using Calculated Dimensions as the harmonization method for creating the Objective field?
A. Scalability - future data streams that will follow similar logic will be automatically harmonized.
B. Data model restrictions - Calculated Dimensions do not need to adhere to Marketing Cloud Intelligence's data model
C. Processing - creation of Calculated Dimensions will ease the processing time of the data streams it relates to
D. Ease of Maintenance - the logic is written and populated in one centralized place
E. Performance (Performance when loading a dashboard page) should be optimized as the values of calculated dimensions are stored within the database.


A. Scalability - future data streams that will follow similar logic will be automatically harmonized.
D. Ease of Maintenance - the logic is written and populated in one centralized place
E. Performance (Performance when loading a dashboard page) should be optimized as the values of calculated dimensions are stored within the database.

Explanation: Scalability: Using Calculated Dimensions allows the client to apply the same harmonization logic to future data streams, ensuring consistency and reducing the need for individual adjustments.
Ease of Maintenance: With the logic centralized in Calculated Dimensions, any adjustments or updates are applied in one place, simplifying ongoing management.
Performance: Calculated Dimensions can improve dashboard performance because their values are pre-computed and stored, reducing the need for real-time calculations when loading dashboards.

Question # 8
Your client would like to create a new harmonization field - Exam Topic. The below table represents the harmonization logic from each source.



Which harmonization feature should an Implementation engineer use to meet the client's requirement?
A. Transformers
B. Parent Chile
C. Fusion
D. Custom Classification
E. Calculated dimensions


D. Custom Classification

Explanation: To meet the client's requirement of slicing measurements by 'Exam Topic' values, an Implementation Engineer should use Custom Classification. This feature allows different Exam IDs to be classified into their respective Exam Topics, ensuring that data from all sources can be accurately harmonized and analyzed based on these topics.

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Salesforce Marketing-Cloud-Intelligence Exam Dumps

Exam Name: Marketing Cloud Intelligence Accredited Professional
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