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Salesforce Marketing-Cloud-Intelligence Official Cert Guide PDF

NEW QUESTION # 17
Which three statements describe Overarching Entities? 03m 23s

• A. Some overarching entities hold a Many-to-Many relationship with the main entity, and others hold a One-to-Many relationship with it.
• B. Once the data streams in which Custom Classification values were mapped are deleted, their data is deleted.
• C. When needed, these entities can act as a main entity, replacing the original one.
• D. The values of these entities are stored at the workspace level, rather than the data stream level
• E. These are mappable dimensions that are present in each and every dataset type

Answer: A,C,D

Explanation:
Overarching Entities in Salesforce Marketing Cloud Intelligence are designed to provide a high level of data organization that spans across multiple data streams. The key points about Overarching Entities are:
* B. Relationship Types: Overarching entities can have either a Many-to-Many or One-to-Many relationship with the main entity, which allows for flexible data modeling and relationship definitions based on the nature of the data and how it should be analyzed and reported.
* C. Acting as Main Entity: They can serve as a main entity in certain situations, enabling a shift in perspective for data analysis. This can be particularly useful when there is a need to view data from a different dimension that is more aligned with business requirements.
* E. Storage Level: The values of these entities are not tied to any single data stream but are maintained at a workspace level, ensuring that they can be applied consistently across different datasets, which is critical for maintaining data integrity and ensuring that classifications are applied uniformly.

NEW QUESTION # 18
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.
The client would like to have a "Site Revenue" measurement.
This measurement should return the highest revenue value per Site, for example:
For Site Key 'SK_C_2', the "Site Revenue" should be $7.00.
When aggregated by date, the "Site Revenue" measurement should return the total sum of the results of all sites.
For example:
For the date 1 Apr 2020, "Site Revenue" should be $11.00 (sum of Site Revenue for Site Keys 'SK_C_1' ($4.00) and 'SK_C_2' ($7.00))

Which options will yield the desired result;

• A. Option #2 & Option #4
• B. Option #2 & Option #3
• C. Option #1 & Option #3
• D. Option #1 & Option #4

Answer: A

Explanation:
* Option #2: It suggests using the 'SUM' function to aggregate the 'Site Revenue' for each 'Site Key'. This is necessary to ensure that when aggregated by date, 'Site Revenue' should return the total sum of the highest revenue for all sites.
* Option #4: It indicates changing the Aggregation Function of Revenue to 'MAX' within Data Stream C.
This ensures that for a given 'Site Key', the highest revenue value is selected, which is correct for
* individual site revenue determination.
Combining Option #2 and Option #4 will provide the desired result:
* For an individual 'Site Key', it will give the highest revenue (using MAX aggregation in Option #4).
* When aggregating by date across all 'Site Key's, it will sum the highest revenues (using the SUM function in Option #2).

NEW QUESTION # 19
Aclient'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 B
• B. Data Stream C
• C. Any of the data streams can technically be the parent
• D. Data Stream A

Answer: B

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.

NEW QUESTION # 20
What Is a disadvantage of using a Vlookup formula?

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

Answer: B

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 # 21
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
"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
7th - 10th. How many different stages are presented in the table?

• A. 0
• B. 1
• C. 2
• D. 3

Answer: A

Explanation:
Based on the Opportunity file and considering the filter dates from January 7th to 10th, the different stages presented are 'Interest', 'Confirmed Interest', and 'Registered'. This makes a total of 3 different stages that would be presented in the pivot table. Salesforce Marketing CloudIntelligence allows for the creation of pivot tables that can display counts of entities across different dimensions, in this case, Opportunity Stages.
Reference to Salesforce Marketing Cloud Intelligence documentation that covers data mapping and pivot table creation would support this conclusion.

NEW QUESTION # 22
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. 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.
• B. Upload the two files and create a Parent-Child relationship between them. The Override Media Buy Hierarchy checkbox is checked in Google Analytics.
• C. 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.
• D. 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.

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 # 23
A client wants to integrate their data within Marketing Cloud Intelligence to optimize their marketing insights and cross-channel marketing activityanalysis. Below are details regarding the different data sources and the number of data streams required for each source.

What three advantages are gained when using Patterns & Data Classification as the harmonization method for creating the Objective field?

• A. Scalability
• B. Use of code
• C. Performance (Performance when loading a dashboard page)
• D. Processing (processing time when loading relevant data streams)
• E. Ease of Maintenance

Answer: A,C,E

Explanation:
Patterns & Data Classification in Marketing Cloud Intelligence offer several advantages. These include:
* Ease of Maintenance (A):Patterns allow for the standardization of data harmonization processes. Once set up, they can be easily maintained and adjusted as needed, without having to manipulate each data stream individually.
* Performance (B):By using patterns, data is classified and standardized at ingestion, which can improve the performance of dashboard page loading because the system does not need to perform complex, on-the-fly calculations or transformations.
* Scalability (D):Patterns can be applied across multiple data streams consistently, allowing them to scale with the data. This means that as the amount of data grows or as new data sources are added, the same patterns can be reused, ensuring that the data remains harmonized.

NEW QUESTION # 24
After uploading a standard file into Marketing Cloud intelligence via totalConnect, you noticed that the number of rows uploaded (to the specific data stream) is NOT equal to the number of rows present in the source file. What are two resource that may cause thisgap?

• A. The source file does not contain the mediaBuy entity
• B. All mapped Measurements for a given row have values equal to zero
• C. Main entity is not mapped
• D. The file does not contain any measurements (dimension only)

Answer: B,C

Explanation:
In Marketing Cloud Intelligence, discrepancies between the number of rows uploaded and the number of rows present in the source file can be caused by several factors. If all mapped measurements for a row are zero, that row may be excluded from the upload, as it does not contribute to the analytics. Additionally, if the main entity, which acts as the primary identifier for records, is not mapped, the system cannot correctly ingest the data as it lacks the necessary reference to organize and store the information.

NEW QUESTION # 25
Your client would like to create a new harmonization field - Exam Topic.
The below table represents the harmonization logic from each source.

As can be seen from the table, there are in fact two fields that hold a certain connection: Exam ID and Exam Topic. The connection indicates that where an Exam ID is found - a single Exam Topic value is associated with it.
The client has a requirement to be able to view measurements from all data sources sliced by Exam Topic values, as seen in the following example:

The client suggested to create, without any mapping manipulations, several patterns via the harmonization center that will generate two Harmonized Dimensions:
Exam ID
Exam Topic
Given the above information, which statement is correct regarding the ability to implement this request with the above suggestion?

• A. Only if 5 different Patterns are created, from 5 different fields - the solution will work.
• B. The solution will work - the client will be able to view Exam Topic with Email Sends.
• C. The Harmonized field for Exam ID is redundant. One Harmonized dimension for Exam Topic is enough for a sustainable and working solution
• D. The above Patterns setup will not work for this use case.

Answer: C

Explanation:
If the harmonization logic consistently associates a single Exam Topic with each Exam ID across all data sources, then creating two harmonized dimensions may be unnecessary. One harmonized dimension for Exam Topic would suffice because it inherently carries the Exam ID's uniqueness within it. The harmonized dimension for Exam Topic would allow the client to slice the data by Exam Topic values, fulfilling the requirement.

NEW QUESTION # 26
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. No mappable measurements - all measurements are calculated
• C. The data is stored at the workspace level.
• D. Pacing - daily rows are being created for every lead and opportunity keys

Answer: B,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 # 27
Which two statements are correct regarding variable Dimensions in marketing Cloud intelligence's data model?

• A. These dimensions are stored at the workspace level
• B. Variable Dimensions hold a Many-to-Many relationship with its main entity
• C. These are stand alone dimensions that pertain to the data set itself rather than to a specific entity
• D. All variables exist in every data set type, hence are considered as overarching dimensions

Answer: A,B

Explanation:
Variable dimensions in Marketing Cloud Intelligence's data model are flexible and can be associated with multiple entities, forming a many-to-many relationship. These dimensions are configured and stored at the workspace level, allowing for customization and alignment with specific reporting needs and analytics practices.

NEW QUESTION # 28
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?

• A. Confirmed Interest & Registered
• B. interest
• C. Confirmed interest
• D. Interest & Registered

Answer: D

Explanation:
Filtering the pivot table on January 7th-11th, we see that the Opportunity Key 123AA01 appears on January
6th with the stage 'Interest' and then on January 10th with the stage 'Registered'. Even though the 'Interest' stage is not within the filtered dates, it is the initial stage of the opportunity, so it should be counted along with the 'Registered' stage which falls within the filter range.

NEW QUESTION # 29
Your client is interested in ingested the below file to a new generic data stream type:

The field 'Meeting Code' was mapped to the main entity key. 'How should the 'Room Number' be mapped?

• A. A custom metric and set aggregation to AUTO
• B. An attribute of 'Meeting Code'
• C. A separate entity key
• D. A custom metric and set aggregation to SUM

Answer: B

Explanation:
In Marketing Cloud Intelligence, when a field is mapped to the main entity key, other related fields should be mapped as attributes of that key if they provide additional descriptors or details. Since 'Room Number' is related to 'Meeting Code', it would be an attribute of the'Meeting Code' entity, providing additional context to the meetings without serving as a metric or a separate entity key.

NEW QUESTION # 30
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. Ease of Maintenance
• B. Scalability
• C. Ease of Setup
• D. Performance (Performance when loading a dashboard page)

Answer: A

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 # 31
An implementation engineer has been asked to perform QA for a standard file ingestion, done by the client.
The source file that was ingested can be seen below:

The number of rows added to this data stream is 3. What could have led to this discrepancy?

• A. All fields are mapped except for the Media Buy Key.
• B. All fields are mapped except for the Media Buy Name.
• C. All fields are mapped except for the Creative Name
• D. All fields are mapped except for the Campaign Key

Answer: D

Explanation:
The source file shows data related to media buys, including a 'Media Buy Key', 'Media Buy Name', 'Campaign Key', and 'Site Key', among other fields. If only three rows were added, and the discrepancy is due to a missing field, it's likely that 'Campaign Key' is the field not mapped, because it is crucial for linking related records in the data stream. Without the 'Campaign Key', the system cannot associate the media buy data with specific campaigns, leading to a potential loss of data rows during ingestion.

NEW QUESTION # 32
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.
* Data Stream C was set as a 'Parent', and the 'Override Media Buy Hierarchy' checkbox is checked What should the Data Updates Permissions be set to for Data Stream B?

• A. Update Attributes
• B. Update Attributes and Hierarchies
• C. Inherit Attributes and Hierarchies
• D. There is no difference, all permissions will have a similar effect given the scenario.

Answer: B

Explanation:
With Data Stream C set as the 'Parent' and 'Override Media Buy Hierarchy' checked:
* The appropriate setting for Data Stream B would be 'Update Attributes and Hierarchies'. This setting will ensure that the hierarchy and attributes from the parent data stream (C) are updated based on the child data stream (B) without overwriting the measurement data that the parent is the source of truth for.
* The 'Override Media Buy Hierarchy' option checked indicates that the hierarchy of the parent is to be considered as the main one, but the attributes and hierarchy can still be updated from the child data stream, which aligns with option B.

NEW QUESTION # 33
Which three statements accurately describe the different data stream types in Marketing Cloud intelligence?

• A. Each data stream type has Its own main entity
• B. Each data stream type has its own set of measurements
• C. All data stream types consist of at least one entity
• D. Every data stream type includes the Medio Buy entity
• E. All data stream types share at least one mutual measurement

Answer: A,B,C

Explanation:
In Marketing Cloud Intelligence, data stream types are templates that define how data should be structured within the system. Each data stream type:
* B.Includes at least one entity, which is a fundamental component of the data stream and represents a collection of related data points.
* D.Has its own main entity, which is the primary focus of that particular data stream type and serves as the central point of reference for the associated data.
* E.Contains its own unique set of measurements that are specific to the type of data being captured within that stream. These measurements represent quantitative data that can be analyzed within the context of the main entity and other dimensions present in the data stream.
A is incorrect because not every data stream type includes the Media Buy entity-this is specific to certain types of advertising data streams. C is incorrect because not all data stream types share at least one mutual measurement; measurements are typically unique to the data stream's focus and purpose.

NEW QUESTION # 34
Aclient has integrated the following files:
File A:

File B:

The client would like to link the two files in order to view the two KPIs ('Tasks Completed' and 'Tasks Assigned) alongside 'Employee Name' and/or
'Squad'.
The client set the following properties:
+ File Ais set as the Parent data stream
* Both files were uploaded to a generic data stream type.
* Override Media Buy Hierarchies is checked for file A.
* The 'Data Updates Permissions' set for file B is 'Update Attributes and Hierarchy'.
When filtering on the entire date range (1-30/8), and querying employee ID, Name and Squad with the two measurements - what will the result look like?

• A.
• B.
• C.
• D.

Answer: A

Explanation:
In Marketing Cloud Intelligence, when linking two data streams, the parent data stream (File A) provides the main structure. Since 'Override Media Buy Hierarchies' is checked for File A, the hierarchies from File B will be aligned with File A. Given 'Data UpdatesPermissions' set for file B as 'Update Attributes and Hierarchy', this means that attributes and hierarchy will be updated in the parent file based on the child file (File B), but the child file's metrics won't be associated with the parent file's date.
Hence, when filtering on the entire date range (1-30/8), the resulting view will align with the structure of the parent data stream, showing the KPIs ('Tasks Completed' from File A and 'Tasks Assigned' from File B) alongside the employee names and squads from the respective files. Since the employee IDs align, the data can be linked properly. However, since the dates do not align (File A data is from 01/08/2019 and File B from
15/08/2019), only attributes from File B will be updated without date association.
The result will look like Option C, where the employee names are corrected based on File B's data, the squads are added from File B, and the tasks_completed and tasks_assigned are displayed from their respective files.
The tasks_assigned from File B are shown without date association as File B's date doesn't match with File A's.

NEW QUESTION # 35
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. This is not possible as the naming conventions are in different fields (Campaign Name and Placement Name)
• C. The client will be able to do this and it will require building three patterns.
• D. it is not possible to do this, as the naming conventions are different

Answer: C

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.

NEW QUESTION # 36
Which two statements are correct regarding the Parent-Child configuration?

• A. A Parent-Child cannot be configured between an Ads data stream type and a Conversion Tag one.
• B. Parent-Child allows sharing both dimensions and measurements
• C. Parent-Child configurations can cause performances issues
• D. Parent-Child links different tables based on shared key values

Answer: C,D

Explanation:
Parent-Child configurations in Marketing Cloud Intelligence are used to link different data tables based on shared key values, allowing for the relational organization of data across variousstreams. While this setup enhances data analysis and reporting by maintaining logical relationships between parent and child tables, it can also introduce performance issues. The complexity increases with the number of relationships and the volume of data, potentially slowing down query processing and data manipulation. Additionally, Parent-Child configurations facilitate the sharing of dimensions and measurements across linked tables, enhancing the data's usability without duplicating it.

NEW QUESTION # 37
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