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Question # 1



A user Is not seeing suggested values from newly-modeled data when building a segment. What is causing this issue?
A. Value suggestion will only return results for the first 50 values of a specific attribute,
B. Value suggestion can only work on direct attributes and not related attributes.
C. Value suggestion requires Data Aware Specialist permissions at a minimum.
D. Value suggestion is still processing and takes up to 24 hours to be available.



D.
  Value suggestion is still processing and takes up to 24 hours to be available.





Question # 2



Cloud Kicks received a Request to be Forgotten by a customer. In which two ways should a consultant use Data Cloud to honor this request? Choose 2 answers
A. Delete the data from the incoming data stream and perform a full refresh.
B. Add the Individual ID to a headerless file and use the delete from file functionality.
C. Use Data Explorer to locate and manually remove the Individual.
D. Use the Consent API to suppress processing and delete the Individual and related records from source data streams.



B.
  Add the Individual ID to a headerless file and use the delete from file functionality.


D.
  Use the Consent API to suppress processing and delete the Individual and related records from source data streams.

Explanation:
To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity’s identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:
Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.
Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:
Delete Individuals from Data Cloud Requesting Data Deletion or Right to Be Forgotten Data Refresh for Data Cloud [Data Explorer]




Question # 3



A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM. This custom object stores the email address a Contact that they want to use for activation. To which data entity is mapped?
A. Contact
B. Contact Point_Email
C. Custom customer Email c object
D. Individual



B.
  Contact Point_Email

Explanation:
The Contact Point_Email object is the data entity that represents an email address associated with an individual in Data Cloud. It is part of the Customer 360 Data Model, which is a standardized data model that defines common entities and relationships for customer data. The Contact Point_Email object can be mapped to any custom or standard object that stores email addresses in Salesforce CRM, such as the custom Customer Email c object. The other options are not the correct data entities to map to because:
A. The Contact object is the data entity that represents a person who is associated with an account that is a customer, partner, or competitor in Salesforce CRM. It is not the data entity that represents an email address in Data Cloud.
C. The custom Customer Email c object is not a data entity in Data Cloud, but a custom object in Salesforce CRM. It can be mapped to a data entity in Data Cloud, such as the Contact Point_Email object, but it is not a data entity itself.
D. The Individual object is the data entity that represents a unique person in Data Cloud. It is the core entity for managing consent and privacy preferences, and it can be related to one or more contact points, such as email addresses, phone numbers, or social media handles. It is not the data entity that represents an email address in Data Cloud.
References:
Customer 360 Data Model: Individual and Contact Points - Salesforce, Contact Point_Email | Object Reference for the Salesforce Platform | Salesforce Developers, [Contact | Object Reference for the Salesforce Platform | Salesforce Developers], [Individual | Object Reference for the Salesforce Platform | Salesforce Developers]




Question # 4



A consultant is integrating an Amazon 53 activated campaign with the customer's destination system. In order for the destination system to find the metadata about the segment, which file on the 53 will contain this information for processing?
A. The .txt file
B. The json file
C. The .csv file
D. The .zip file



B.
  The json file

Explanation:
The file on the Amazon S3 that will contain the metadata about the segment for processing is B. The json file. The json file is a metadata file that is generated along with the csv file when a segment is activated to Amazon S3. The json file contains information such as the segment name, the segment ID, the segment size, the segment attributes, the segment filters, and the segment schedule. The destination system can use this file to identify the segment and its properties, and to match the segment data with the corresponding fields in the destination system.
References:
Salesforce Data Cloud Consultant Exam Guide, Amazon S3 Activation




Question # 5



Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in real time and send out a notification as soon as it detects volume outside a customer's normal range. What should a consultant do to accommodate this request?
A. Use a calculated insight paired with a flow.
B. Use streaming data transform with a flow.
C. Use a streaming insight paired with a data action
D. Use streaming data transform combined with a data action.



C.
  Use a streaming insight paired with a data action

Explanation:
A streaming insight is a type of insight that analyzes streaming data in real time and triggers actions based on predefined conditions. A data action is a type of action that executes a flow, a data action target, or a data action script when an insight is triggered. By using a streaming insight paired with a data action, a consultant can accommodate Cumulus Financial’s request to track the daily transaction volume of each customer and send out a notification when the volume is outside the normal range. A calculated insight is a type of insight that performs calculations on data in a data space and stores the results in a data extension. A streaming data transform is a type of data transform that applies transformations to streaming data in real time and stores the results in a data extension. A flow is a type of automation that executes a series of actions when triggered by an event, a schedule, or another flow. None of these options can achieve the same functionality as a streaming insight paired with a data action.
References:
Use Insights in Data Cloud Unit, Streaming Insights and Data Actions Use Cases, Streaming Insights and Data Actions Limits and Behaviors




Question # 6



To import campaign members into a campaign in Salesforce CRM, a user wants to export the segment to Amazon S3. The resulting file needs to include the Salesforce CRM Campaign ID in the name. What are two ways to achieve this outcome? Choose 2 answers
A. Include campaign identifier in the activation name.
B. Hard code the campaign identifier as a new attribute in the campaign activation.
C. Include campaign identifier in the filename specification.
D. Include campaign identifier in the segment name.



A.
  Include campaign identifier in the activation name.


C.
  Include campaign identifier in the filename specification.

Explanation:
The two ways to achieve this outcome are A and C. Include campaign identifier in the activation name and include campaign identifier in the filename specification. These two options allow the user to specify the Salesforce CRM Campaign ID in the name of the file that is exported to Amazon S3. The activation name and the filename specification are both configurable settings in the activation wizard, where the user can enter the campaign identifier as a text or a variable. The activation name is used as the prefix of the filename, and the filename specification is used as the suffix of the filename. For example, if the activation name is “Campaign_123” and the filename specification is “{segmentName}_{date}”, the resulting file name will be “Campaign_123_SegmentA_2023-12-18.csv”. This way, the user can easily identify the file that corresponds to the campaign and import it into Salesforce CRM.
The other options are not correct. Option B is incorrect because hard coding the campaign identifier as a new attribute in the campaign activation is not possible. The campaign activation does not have any attributes, only settings. Option D is incorrect because including the campaign identifier in the segment name is not sufficient. The segment name is not used in the filename of the exported file, unless it is specified in the filename specification. Therefore, the user will not be able to see the campaign identifier in the file name.




Question # 7



Which two steps should a consultant take if a successfully configured Amazon S3 data stream fails to refresh with a "NO FILE FOUND" error message? Choose 2 answers
A. Check if correct permissions are configured for the Data Cloud user.
B. Check if the Amazon S3 data source is enabled in Data Cloud Setup.
C. Check If the file exists in the specified bucket location.
D. Check if correct permissions are configured for the S3 user.



A.
  Check if correct permissions are configured for the Data Cloud user.


C.
  Check If the file exists in the specified bucket location.

Explanation:
A “NO FILE FOUND” error message indicates that Data Cloud cannot access or locate the file from the Amazon S3 source. There are two possible reasons for this error and two corresponding steps that a consultant should take to troubleshoot it:
The Data Cloud user does not have the correct permissions to read the file from the Amazon S3 bucket. This could happen if the user’s permission set or profile does not include the Data Cloud Data Stream Read permission, or if the user’s Amazon S3 credentials are invalid or expired. To fix this issue, the consultant should check and update the user’s permissions and credentials in Data Cloud and Amazon S3, respectively.
The file does not exist in the specified bucket location. This could happen if the file name or path has changed, or if the file has been deleted or moved from the Amazon S3 bucket. To fix this issue, the consultant should check and verify the file name and path in the Amazon S3 bucket, and update the data stream configuration in Data Cloud accordingly.
References:
Create Amazon S3 Data Stream in Data Cloud, How to Use the Amazon S3 Storage Connector in Data Cloud, Amazon S3 Connection




Question # 8



A consultant is building a segment to announce a new product launch for customers that have previously purchased black pants. How should the consultant place attributes for product color and product type from the Order Product object to meet this criteria?
A. Place the attribute for product color in one container and the attribute for product type in another container.
B. Place an attribute for the "black" calculated insight to dynamically apply
C. Place the attributes for product and product type as direct attributes.
D. Place the attributes for product color and product type in a single container.



D.
  Place the attributes for product color and product type in a single container.

Explanation:
To create a segment based on the product color and product type from the Order Product object, the consultant should place the attributes for product color and product type in a single container. This way, the segment will include only the customers who have purchased black pants, and not those who have purchased black shirts or blue pants. A container is a grouping of attributes that defines a segment of individuals based on a logical AND operation. Placing the attributes in separate containers would result in a segment that includes customers who have purchased any black product or any pants product, which is not the desired criteria. Placing an attribute for the “black” calculated insight would not work, because calculated insights are based on aggregated data and not individual-level data. Placing the attributes as direct attributes would not work, because direct attributes are used to filter individuals based on their profile data, not their order data.
References:
Create a Segment in Data Cloud Learn About Segmentation Tools Salesforce Launches: Data Cloud Consultant Certification




Question # 9



A customer has two Data Cloud orgs. A new configuration has been completed and tested for an Amazon S3 data stream and its mappings in one of the Data Cloud orgs. What is recommended to package and promote this configuration to the customer's second org?
A. Use the Metadata API.
B. Use the Salesforce CRM connector.
C. Create a data kit.
D. Package as an AppExchange application.



C.
  Create a data kit.

Explanation:
Data Cloud Configuration Promotion: When managing configurations across multiple Salesforce Data Cloud orgs, it's essential to use tools that ensure consistency and accuracy in the promotion process.
Data Kits: Salesforce Data Cloud allows users to package and promote configurations using data kits. These kits encapsulate data stream definitions, mappings, and other configuration elements into a portable format.
Process:
Create a data kit in the source org that includes the Amazon S3 data stream configuration and mappings.
Export the data kit from the source org.
Import the data kit into the target org, ensuring that all configurations are transferred accurately.
Advantages: Using data kits simplifies the migration process, reduces the risk of configuration errors, and ensures that all settings and mappings are consistently applied in the new org.
References:
Salesforce Data Cloud Developer Guide Salesforce Data Cloud Packaging




Question # 10



A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers. Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?
A. Party Identification object
B. Loyalty Identification object
C. Individual object
D. Contact Identification object



A.
  Party Identification object

Explanation:
The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals. The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.
References:
Data Modeling Requirements for Identity Resolution Identity Resolution in a Data Space
Configure Identity Resolution Rulesets Map Required Objects
Data and Identity in Data Cloud



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Salesforce Certified Data Cloud Consultant (SU24) Exam Dumps


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