2025年最新の100%無料Data-Cloud-Consultant日常練習試験には164問があります
Data-Cloud-Consultant試験資料Salesforce学習ガイド
Salesforce Data-Cloud-Consultant 認定試験の出題範囲：
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質問 # 84
A customer needs to integrate in real time with Salesforce CRM.
Which feature accomplishes this requirement?
- A. Streaming transforms
- B. Sales and Service bundle
- C. Data actions and Lightning web components
- D. Data model triggers
正解：A
解説：
The correct answer is A. Streaming transforms. Streaming transforms are a feature of Data Cloud that allows real-time data integration with Salesforce CRM. Streaming transforms use the Data Cloud Streaming API to synchronize micro-batches of updates between the CRM data source and Data Cloud in near-real time1. Streaming transforms enable Data Cloud to have the most current and accurate CRM data for segmentation and activation2.
The other options are incorrect for the following reasons:
* B. Data model triggers. Data model triggers are a feature of Data Cloud that allows custom logic to be executed when data model objects are created, updated, or deleted3. Data model triggers do not integrate data with Salesforce CRM, but rather manipulate data within Data Cloud.
* C. Sales and Service bundle. Sales and Service bundle is a feature of Data Cloud that allows pre-built data streams, data model objects, segments, and activations for Sales Cloud and Service Cloud data sources4. Sales and Service bundle does not integrate data in real time with Salesforce CRM, but rather ingests data at scheduled intervals.
* D. Data actions and Lightning web components. Data actions and Lightning web components are features of Data Cloud that allow custom user interfaces and workflows to be built and embedded in Salesforce applications5. Data actions and Lightning web components do not integrate data with Salesforce CRM, but rather display and interact with data within Salesforce applications.
References:
* 1: Load Data into Data Cloud
* 2: [Data Streams in Data Cloud]
* 3: [Data Model Triggers in Data Cloud] unit on Trailhead
* 4: [Sales and Service Bundle in Data Cloud] unit on Trailhead
* 5: [Data Actions and Lightning Web Components in Data Cloud] unit on Trailhead
* : [Data Model in Data Cloud] unit on Trailhead
* : [Create a Data Model Object] article on Salesforce Help
* : [Data Sources in Data Cloud] unit on Trailhead
* : [Connect and Ingest Data in Data Cloud] article on Salesforce Help
* : [Data Spaces in Data Cloud] unit on Trailhead
* : [Create a Data Space] article on Salesforce Help
* : [Segments in Data Cloud] unit on Trailhead
* : [Create a Segment] article on Salesforce Help
* : [Activations in Data Cloud] unit on Trailhead
* : [Create an Activation] article on Salesforce Help
質問 # 85
A customer has multiple team members who create segment audiences that work in different time zones. One team member works at the home office in the Pacific time zone, that matches the org Time Zone setting. Another team member works remotely in the Eastern time zone.
Which user will see their home time zone in the segment and activation schedule areas?
- A. Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user
- B. The team member in the Pacific time zone.
- C. Neither team member; Data Cloud shows all schedules in GMT.
- D. The team member in the Eastern time zone.
正解：A
解説：
The correct answer is D, both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user. Data Cloud uses the time zone settings of the logged-in user to display the segment and activation schedules. This means that each user will see the schedules in their own home time zone, regardless of the org time zone setting or the location of other team members. This feature helps users to avoid confusion and errors when scheduling segments and activations across different time zones. The other options are incorrect because they do not reflect how Data Cloud handles time zones. The team member in the Pacific time zone will not see the same time zone as the org time zone setting, unless their personal time zone setting matches the org time zone setting. The team member in the Eastern time zone will not see the schedules in the org time zone setting, unless their personal time zone setting matches the org time zone setting. Data Cloud does not show all schedules in GMT, but rather in the user's local time zone. Reference:
Data Cloud Time Zones
Change default time zones for Users and the organization
Change your time zone settings in Salesforce, Google & Outlook
DateTime field and Time Zone Settings in Salesforce
質問 # 86
What does the Source Sequence reconciliation rule do in identity resolution?
- A. Includes data from sources where the data is most frequently occurring
- B. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name
- C. Identifies which data sources should be used in the process of reconcillation by prioritizing the most recently updated data source
- D. Identifies which individual records should be merged into a unified profile by setting a priority for specific data sources
正解：B
解説：
The Source Sequence reconciliation rule sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name. This rule allows you to define which data source should be used as the primary source of truth for each attribute, and which data sources should be used as fallbacks in case the primary source is missing or invalid. For example, you can set the Source Sequence rule to use data from Salesforce CRM as the first priority, data from Marketing Cloud as the second priority, and data from Google Analytics as the third priority for the first name attribute. This way, the unified profile will use the first name value from Salesforce CRM if it exists, otherwise it will use the value from Marketing Cloud, and so on. This rule helps you to ensure the accuracy and consistency of the unified profile attributes across different data sources. References: Salesforce Data Cloud Consultant Exam Guide, Identity Resolution, Reconciliation Rules
質問 # 87
How does Data Cloud handle an individual's Right to be Forgotten?
- A. Deletes the specified Individual and records from any data model object/data lake object related to the Individual.
- B. Deletes the specified Individual record and its Unified Individual Link record.
- C. Deletes the records from all data source objects, and any downstream data model objects are updated at the next scheduled ingestion
- D. Deletes the specified Individual and records from any data source object mapped to the Individual data model object.
正解：A
解説：
Data Cloud handles an individual's Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.
The other options are not correct descriptions of how Data Cloud handles an individual's Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.
Reference:
Requesting Data Deletion or Right to Be Forgotten
Data Deletion for Data Cloud
Use the Consent API with Data Cloud
Data and Identity in Data Cloud
質問 # 88
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers
- A. The primary key of the segmented table must be a dimension in the calculated insight.
- B. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
- C. The metrics of the calculated insights must only contain numeric values.
- D. The primary key of the segmented table must be a metric in the calculated insight.
正解：A、B
解説：
Explanation
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
* The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location.
The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud.
The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
* The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
References: Create a Calculated Insight, Use Insights in Data Cloud, Segmentation
質問 # 89
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
- A. Confirm the Create object permission is enabled in the Data Cloud org.
- B. Confirm that the Modify Object permission is enabled in the Data Cloud org.
- C. Confirm the Ingest Object permission is enabled in the Salesforce CRM org.
- D. Confirm the View All object permission is enabled in the source Salesforce CRM org.
正解：D
解説：
To create a new data stream from a custom Salesforce CRM object, the consultant needs to confirm that the View All object permission is enabled in the source Salesforce CRM org. This permission allows the user to view all records associated with the object, regardless of sharing settings1. Without this permission, the custom object will not be available in the New Data Stream configuration2. References:
* Manage Access with Data Cloud Permission Sets
* Object Permissions
質問 # 90
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 Point_Email
- B. Custom customer Email__c object
- C. Contact
- D. Individual
正解：A
解説：
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]
質問 # 91
Cumulus Financial uses calculated insights to compute the total banking value per branch for its high net worth customers. In the calculated insight, "banking value" is a metric, "branch" is a dimension, and "high net worth" is a filter.
What can be included as an attribute in activation?
- A. "banking value" (metric)
- B. "branch" (dimension)
- C. "high net worth" (filter)
- D. "branch" (dimension) and "banking metric)
正解：B
解説：
According to the Salesforce Data Cloud documentation, an attribute is a dimension or a measure that can be used in activation. A dimension is a categorical variable that can be used to group or filter data, such as branch, region, or product. A measure is a numerical variable that can be used to calculate metrics, such as revenue, profit, or count. A filter is a condition that can be applied to limit the data that is used in a calculated insight, such as high net worth, age range, or gender. In this question, the calculated insight uses "banking value" as a metric, which is a measure, and "branch" as a dimension. Therefore, only "branch" can be included as an attribute in activation, since it is a dimension. The other options are either measures or filters, which are not attributes. Reference: Data Cloud Permission Sets, Salesforce Data Cloud Exam Questions
質問 # 92
Northern Trail Outfitters is using the Marketing Cloud Starter Data Bundles to bring Marketing Cloud data into Data Cloud.
What are two of the available datasets in Marketing Cloud Starter Data Bundles?
Choose 2 answers
- A. Personalization
- B. MobileConnect
- C. MobilePush
- D. Loyalty Management
正解：B、C
解説：
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyalty programs for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
質問 # 93
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 Point_Email
- B. Custom customer Email__c object
- C. Contact
- D. Individual
正解：A
解説：
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. Reference: 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]
質問 # 94
Which consideration related to the way Data Cloud ingests CRM data is true?
- A. The CRM Connector's synchronization times can be customized to up to 15-minute intervals.
- B. The CRM Connector allows standard fields to stream into Data Cloud in real time.
- C. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization,
- D. Formula fields are refreshed at regular sync intervals and are updated at the next full refresh.
正解：B
解説：
Explanation
The correct answer is D. The CRM Connector allows standard fields to stream into Data Cloud in real time.
This means that any changes to the standard fields in the CRM data source are reflected in Data Cloud almost instantly, without waiting for the next scheduled synchronization. This feature enables Data Cloud to have the most up-to-date and accurate CRM data for segmentation and activation1.
The other options are incorrect for the following reasons:
* A. CRM data can be manually refreshed at any time by clicking the Refresh button on the data stream detail page2. This option is false.
* B. The CRM Connector's synchronization times can be customized to up to 60-minute intervals, not
15-minute intervals3. This option is false.
* C. Formula fields are not refreshed at regular sync intervals, but only at the next full refresh4. A full refresh is a complete data ingestion process that occurs once every 24 hours or when manually triggered.
This option is false.
References:
* 1: Connect and Ingest Data in Data Cloud article on Salesforce Help
* 2: Data Sources in Data Cloud unit on Trailhead
* 3: Data Cloud for Admins module on Trailhead
* 4: [Formula Fields in Data Cloud] unit on Trailhead
* : [Data Streams in Data Cloud] unit on Trailhead
質問 # 95
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. Use Data Explorer to locate and manually remove the Individual.
- B. Add the Individual ID to a headerless file and use the delete from file functionality.
- C. Use the Consent API to suppress processing and delete the Individual and related records from source data streams.
- D. Delete the data from the incoming data stream and perform a full refresh.
正解：B、C
解説：
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]
質問 # 96
What should an organization use to stream inventory levels from an inventory management system into Data Cloud in a fast and scalable, near-real-time way?
- A. Ingestion API
- B. Commerce Cloud Connector
- C. Cloud Storage Connector
- D. Marketing Cloud Personalization Connector
正解：A
解説：
The Ingestion API is a RESTful API that allows you to stream data from any source into Data Cloud in a fast and scalable way. You can use the Ingestion API to send data from your inventory management system into Data Cloud as JSON objects, and then use Data Cloud to create data models, segments, and insights based on your inventory data. The Ingestion API supports both batch and streaming modes, and can handle up to
100,000 records per second. The Ingestion API also provides features such as data validation, encryption, compression, and retry mechanisms to ensure data quality and security. References: Ingestion API Developer Guide, Ingest Data into Data Cloud
質問 # 97
Northern Trail Outfitters asks its consultant to extract the runner profiles and activity logs from its Track My Run mobile app and load them into Data Cloud. The marketing department also indicates that they need the last 90 days of historical data and want all new and updated data as it becomes available on a go-forward basis.
As best practice, which sequence of actions should the consultant use to implement this request?
- A. Use streaming ingestion to first load the last 90 days of data, and then use bulk Ingestion to synchronize future data as It becomes available.
- B. Use streaming ingestion to first load the last 90 days of data, and also subsequently use streaming ingestion synchronize future data as It becomes available.
- C. Use bulk ingestion to first load the last 90 days of data, and then use streaming ingestion to synchronize future data as It becomes available.
- D. Use bulk ingestion to first load the last 90 days of data, and also subsequently use bulk ingestion to synchronize the future data as It becomes available.
正解：C
解説：
Initial Data Load: For loading large volumes of historical data, such as the last 90 days of runner profiles and activity logs, bulk ingestion is the most efficient method. It allows for high-throughput data transfer.
* Bulk Ingestion: Use Salesforce Data Cloud's bulk ingestion tools to load the historical data quickly and efficiently.
Ongoing Data Synchronization: To keep the Data Cloud updated with new and modified records as they become available in the Track My Run mobile app, streaming ingestion is appropriate. It ensures near-real-time data updates.
* Streaming Ingestion: Configure streaming ingestion to continuously update the Data Cloud with new and updated data from the mobile app.
Sequence of Actions:
* Step 1: Perform bulk ingestion to import the last 90 days of historical data into Data Cloud.
* Step 2: Set up streaming ingestion to handle ongoing updates and new data as it becomes available.
Best Practice: This approach ensures that the initial large data load is handled efficiently, and ongoing updates are processed in near real-time, providing the marketing department with the most up-to-date data.
References:
* Salesforce Data Cloud Ingestion Methods
* Salesforce Bulk Data Ingestion
* Salesforce Streaming Data Ingestion
質問 # 98
Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream?
Choose 2 answers
- A. Ensure the filename contains a wildcard to a accommodate the timestamp.
- B. Ensure the refresh mode is set to "Full Refresh.''
- C. Ensure the refresh mode is set to "Upsert".
- D. Ensure that deletion of old files is enabled.
正解：A、C
解説：
When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:
The refresh mode should be set to "Upsert", which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.
The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name is store_transactions_2023-12-18.csv, the wildcard could be store_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.
The other options are not necessary or relevant for this scenario:
Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.
Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result in data loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of transactions. Reference: Ingest Data from Amazon S3, Refresh Modes
質問 # 99
Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream?
Choose 2 answers
- A. Ensure the filename contains a wildcard toa accommodatethe timestamp.
- B. Ensure the refresh mode is set to "Full Refresh.''
- C. Ensure the refresh mode is set to "Upsert".
- D. Ensure that deletion of old files is enabled.
正解：A、C
解説：
Explanation
When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:
* The refresh mode should be set to "Upsert", which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.
* The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name is store_transactions_2023-12-18.csv, the wildcard could be store_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.
The other options are not necessary or relevant for this scenario:
* Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.
* Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result indata loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of
* transactions. References: Ingest Data from Amazon S3, Refresh Modes
質問 # 100
What is Data Cloud's primary value to customers?
- A. To create a single source of truth for all anonymous data
- B. To connect all systems with a golden record
- C. To create personalized campaigns by listening, understanding, and acting on customer behavior
- D. To provide a unified view of a customer and their related data
正解：D
解説：
Explanation
Data Cloud is a platform that enables you to activate all your customer data across Salesforce applications and other systems. Data Cloud allows you to create a unified profile of each customer by ingesting, transforming, and linking data from various sources, such as CRM, marketing, commerce, service, and external data providers. Data Cloud also provides insights and analytics on customer behavior, preferences, and needs, as well as tools to segment, target, and personalize customer interactions. Data Cloud's primary value to customers is to provide a unified view of a customer and their related data, which can help you deliver better customer experiences, increase loyalty, and drive growth. References: Salesforce Data Cloud, When Data Creates Competitive Advantage
質問 # 101
Northern Trail Outfitters unifies individuals in its Data Cloud instance.
Which three features ca e consultant use to validate the data on a unified profile?
Choose 3 answers
- A. Profile Explorer
- B. Data Explorer
- C. Query APL
- D. Identity Resolution
- E. Data Actions
正解：A、B、D
解説：
To validate the data on a unified profile, the consultant can use the following features:
Identity Resolution: This feature allows the consultant to view and edit the identity resolution rulesets that determine how individuals are unified from different data sources1.
Data Explorer: This feature allows the consultant to browse and filter the unified profiles and view their attributes, segments, and activities2.
Profile Explorer: This feature allows the consultant to drill down into a specific unified profile and view its details, such as source records, identity graph, calculated insights, and data actions3. Reference:
1: Identity Resolution in Data Cloud
2: Data Explorer in Data Cloud
3: Profile Explorer in Data Cloud
質問 # 102
A Data CloudConsultantIs in the process of setting up data streams for a new service-based data source.
When ingesting Case data, which field is recommended to be associated with the Event Time field?
- A. Last Modified Date
- B. Escalation Date
- C. Creation Date
- D. Resolution Date
正解：A
解説：
Explanation
The Event Time field is a special field type that captures the timestamp of an event in a data stream. It is used to track the chronological order of events and to enable time-based segmentation and activation. When ingesting Case data, the recommended field to be associated with the Event Time field is the Last Modified Date field. This field reflects the most recent update to the case and can be used to measure the case duration, resolution time, and customer satisfaction. The other fields, such as Resolution Date, Escalation Date, or Creation Date, are not as suitable for the Event Time field, as they may not capture the latest status of the case or may not be applicable for all cases. References: Data Stream Field Types, Salesforce Data Cloud Exam Questions
質問 # 103
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 json file
- B. The .zip file
- C. The .csv file
- D. The .txt file
正解：A
解説：
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
質問 # 104
A customer wants to use the transactional data from their data warehouse in Data Cloud.
They are only able to export the data via an SFTP site.
How should the file be brought into Data Cloud?
- A. Ingest the file through the Cloud Storage Connector.
- B. Use Salesforce's Dataloader application to perform a bulk upload from a desktop.
- C. Manually import the file using the Data Import Wizard.
- D. Ingest the file with the SFTP Connector.
正解：D
解説：
The SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server. The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:
B . The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.
C . The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.
D . The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud. Reference: SFTP Connector - Salesforce, Create Data Streams with the SFTP Connector in Data Cloud - Salesforce, Data Import Wizard - Salesforce, Salesforce Data Loader
質問 # 105
A bank collects customer data for its loan applicants and high net worth customers. A customer can be both a load applicant and a high net worth customer, resulting in duplicate data.
How should a consultant ingest and map this data in Data Cloud?
- A. Ingest the data into two DLOs and map each to the individual and Contact point Email DMOs.
- B. Ingest the data into one DLO and then map to one custom DMO.
- C. Use a data transform to consolidate the data into one DLO and them map it to the individual and Contact Point Email DMOs.
- D. Ingest the data into two DLOs and then map to two custom DMOs.
正解：C
質問 # 106
When performing segmentation or activation, which time zone is used to publish and refresh data?
- A. Time zone of the Data Cloud Admin user
- B. Time zone of the user creating the activity
- C. Time zone specified on the activity at the time of creation
- D. Time zone set by the Salesforce Data Cloud org
正解：D
解説：
The time zone that is used to publish and refresh data when performing segmentation or activation is D. Time zone set by the Salesforce Data Cloud org. This time zone is the one that is configured in the org settings when Data Cloud is provisioned, and it applies to all users and activities in Data Cloud. This time zone determines when the segments are scheduled to refresh and when the activations are scheduled to publish. Therefore, it is important to consider the time zone difference between the Data Cloud org and the destination systems or channels when planning the segmentation and activation strategies. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Activation
質問 # 107
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