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Salesforce Data-Cloud-Consultant Exam Sample Questions

Question # 1

To import campaign members into a campaign in CRM a user wants to export the segment to Amazon S3. The resulting file needs to include CRM Campaign ID in the name. How can this outcome be achieved?

A. Include campaign identifier into the activation name

B. Hard-code the campaign identifier as a new attribute in the campaign activation

C. Include campaign identifier into the filename specification

D. Include campaign identifier into the segment name

Answer

C. Include campaign identifier into the filename specification

Explanation:

You can use the filename specification option in the Amazon S3 activation to customize the name of the file that is exported. You can use variables such as {campaignId} to include the CRM campaign ID in the file name.

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Question # 2

A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud. Where does a request for data deletion or right to be forgotten get submitted?

A. In Data Cloud settings

B. On the individual data profile in Data Cloud

C. In Marketing Cloud settings

D. through Consent API

Answer

C. In Marketing Cloud settings

Explanation: Data Deletion Requests: For companies using Salesforce Marketing Cloud and Data Cloud, managing data privacy and deletion requests is essential. Marketing Cloud Connector: This connector facilitates data integration between Marketing Cloud and Data Cloud, but data deletion requests must follow specific procedures. Deletion Requests in Marketing Cloud: Data Management: Requests for data deletion or the right to be forgotten are submitted through Marketing Cloud settings, where the customer data is originally stored and managed. Propagation: Once the request is processed in Marketing Cloud, the changes are propagated to Data Cloud through the connector. References: Salesforce Marketing Cloud Documentation: Data Management Salesforce Data Cloud Connector Guide

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Question # 3

How can a consultant modify attribute names to match a naming convention in Cloud File Storage targets?

A. Use a formula field to update the field name in an activation.

B. Update attribute names in the data stream configuration.

C. Set preferred attribute names when configuring activation.

D. Update field names in the data model object.

Answer

C. Set preferred attribute names when configuring activation.

Explanation: A Cloud File Storage target is a type of data action target in Data Cloud that allows sending data to a cloud storage service such as Amazon S3 or Google Cloud Storage. When configuring an activation to a Cloud File Storage target, a consultant can modify the attribute names to match a naming convention by setting preferred attribute names in Data Cloud. Preferred attribute names are aliases that can be used to control the field names in the target file. They can be set for each attribute in the activation configuration, and they will override the default field names from the data model object. The other options are incorrect because they do not affect the field names in the target file. Using a formula field to update the field name in an activation will not change the field name, but only the field value. Updating attribute names in the data stream configuration will not affect the existing data lake objects or data model objects. Updating field names in the data model object will change the field names for all data sources and activations that use the object, which may not be desirable or consistent. References: Preferred Attribute Name, Create a Data Cloud Activation Target, Cloud File Storage Target

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Question # 4

Cumulus Financial uses Service Cloud as its CRM and stores mobile phone, home phone, and work phone as three separate fields for its customers on the Contact record. The company plansz to use Data Cloud and ingest the Contact object via the CRM Connector. What is the most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation?

A. Ingest the Contact object and map the Work Phone, Mobile Phone, and Home Phone to the Contact Point Phone data map object from the Contact data stream.

B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object.

C. Ingest the Contact object and then create a calculated insight to normalize the phone numbers, and then map to the Contact Point Phone data map object.

D. Ingest the Contact object and create formula fields in the Contact data stream on the phone numbers, and then map to the Contact Point Phone data map object.

Answer

B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object.

Explanation:

The most efficient approach is B: Ingest the Contact object and use streaming transforms to normalize phone numbers into a separate Phone DLO, which stores each phone number type (work, home, mobile) in three rows. This data is then mapped to the Contact Point Phone object, ensuring all phone numbers are available for activation (e.g., SMS, calls). Streaming transforms allow real-time normalization (removing spaces, dashes, adding country codes) during ingestion without extra processing or storage.

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Question # 5

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.

Answer

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]

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