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Data-Cloud-Consultant問題集PDF最新 [2025年最新] 究極の学習ガイド
質問 # 98
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 the file exists in the specified bucket location.
- B. Check if the Amazon S3 data source is enabled in Data Cloud Setup.
- C. Check if correct permissions are configured for the S3 user.
- D. Check if correct permissions are configured for the Data Cloud user.
正解：A、D
解説：
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
質問 # 99
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 .csv file
- C. The .zip file
- D. The json file
正解：D
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 # 100
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company.
Which action is essential to effectively begin the Data Cloud lifecycle?
- A. Use calculated insights determine the benefits of Data Cloud for this company.
- B. Identify use cases and the required data sources and data quality.
- C. Migrate the existing data into the Customer 360 Data Model.
- D. Analyze and partition the data into data spaces.
正解：B
解説：
* Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
* Identifying Use Cases:
Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
* Actions:
Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
Step 2: Identify and catalog the required data sources for these use cases.
Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
* Reference:
Salesforce Data Cloud Implementation Guide
Salesforce Data Cloud Lifecycle
質問 # 101
Data Cloud receives a nightly file of all ecommerce transactions from the previous day.
Several segments and activations depend upon calculated insights from the updated data in order to maintain accuracy in the customer's scheduled campaign messages.
What should the consultant do to ensure the ecommerce data is ready for use for each of the scheduled activations?
- A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run.
- B. Set a refresh schedule for the calculated insights to occur every hour.
- C. Ensure the segments are set to Rapid Publish and set to refresh every hour.
- D. Ensure the activations are set to Incremental Activation and automatically publish every hour.
正解：A
解説：
The best option that the consultant should do to ensure the ecommerce data is ready for use for each of the scheduled activations is A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run. This option allows the consultant to use the Flow feature of Data Cloud, which enables automation and orchestration of data processing tasks based on events or schedules. Flow can be used to trigger a change data event on the ecommerce data, which is a type of event that indicates that the data has been updated or changed. This event can then trigger the refresh of the calculated insights and segments that depend on the ecommerce data, ensuring that they reflect the latest data. The refresh of the calculated insights and segments can be completed before the activations are scheduled to run, ensuring that the customer's scheduled campaign messages are accurate and relevant.
The other options are not as good as option A. Option B is incorrect because setting a refresh schedule for the calculated insights to occur every hour may not be sufficient or efficient. The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data. The refresh schedule may also consume more resources and time than necessary, as the ecommerce data may not change every hour. Option C is incorrect because ensuring the activations are set to Incremental Activation and automatically publish every hour may not solve the problem. Incremental Activation is a feature that allows only the new or changed records in a segment to be activated, reducing the activation time and size. However, this feature does not ensure that the segment data is updated or refreshed based on the ecommerce data. The activation schedule may also not match the ecommerce data update schedule, resulting in inaccurate or irrelevant campaign messages. Option D is incorrect because ensuring the segments are set to Rapid Publish and set to refresh every hour may not be optimal or effective. Rapid Publish is a feature that allows segments to be published faster by skipping some validation steps, such as checking for duplicate records or invalid values.
However, this feature may compromise the quality or accuracy of the segment data, and may not be suitable for all use cases. The refresh schedule may also have the same issues as option B, as it may not sync with the ecommerce data update schedule or the activation schedule, resulting in outdated or inconsistent data. References: Salesforce Data Cloud Consultant Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]
質問 # 102
Data Cloud receives a nightly file of all ecommerce transactions from the previous day.
Several segments and activations depend upon calculated insights from the updated data in order to maintain accuracy in the customer's scheduled campaign messages.
What should the consultant do to ensure the ecommerce data is ready for use for each of the scheduled activations?
- A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run.
- B. Set a refresh schedule for the calculated insights to occur every hour.
- C. Ensure the segments are set to Rapid Publish and set to refresh every hour.
- D. Ensure the activations are set to Incremental Activation and automatically publish every hour.
正解：A
解説：
The best option that the consultant should do to ensure the ecommerce data is ready for use for each of the scheduled activations is A. Use Flow to trigger a change data event on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run. This option allows the consultant to use the Flow feature of Data Cloud, which enables automation and orchestration of data processing tasks based on events or schedules. Flow can be used to trigger a change data event on the ecommerce data, which is a type of event that indicates that the data has been updated or changed. This event can then trigger the refresh of the calculated insights and segments that depend on the ecommerce data, ensuring that they reflect the latest data. The refresh of the calculated insights and segments can be completed before the activations are scheduled to run, ensuring that the customer's scheduled campaign messages are accurate and relevant.
The other options are not as good as option A. Option B is incorrect because setting a refresh schedule for the calculated insights to occur every hour may not be sufficient or efficient. The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data. The refresh schedule may also consume more resources and time than necessary, as the ecommerce data may not change every hour. Option C is incorrect because ensuring the activations are set to Incremental Activation and automatically publish every hour may not solve the problem. Incremental Activation is a feature that allows only the new or changed records in a segment to be activated, reducing the activation time and size. However, this feature does not ensure that the segment data is updated or refreshed based on the ecommerce data. The activation schedule may also not match the ecommerce data update schedule, resulting in inaccurate or irrelevant campaign messages. Option D is incorrect because ensuring the segments are set to Rapid Publish and set to refresh every hour may not be optimal or effective. Rapid Publish is a feature that allows segments to be published faster by skipping some validation steps, such as checking for duplicate records or invalid values. However, this feature may compromise the quality or accuracy of the segment data, and may not be suitable for all use cases. The refresh schedule may also have the same issues as option B, as it may not sync with the ecommerce data update schedule or the activation schedule, resulting in outdated or inconsistent data. Reference: Salesforce Data Cloud Consultant Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]
質問 # 103
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 records from all data source objects, and any downstream data model objects are updated at the next scheduled ingestion
- C. Deletes the specified Individual and records from any data source object mapped to the Individual data model object.
- D. Deletes the specified Individual record and its Unified Individual Link record.
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.
References:
* 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 # 104
Which operator should a consultant use to create a segment for a birthday campaign that is evaluated daily?
- A. Is Today
- B. Is Birthday
- C. Is Between
- D. Is Anniversary Of
正解：D
解説：
Explanation
To create a segment for a birthday campaign that is evaluated daily, the consultant should use the Is Anniversary Of operator. This operator compares a date field with the current date and returns true if the month and day are the same, regardless of the year. For example, if the date field is 1990-01-01 and the current date is 2023-01-01, the operator returns true. This way, the consultant can create a segment that includes all the customers who have their birthday on the same day as the current date, and the segment will be updated daily with the new birthdays. The other options are not the best operators to use for this purpose because:
* A. The Is Today operator compares a date field with the current date and returns true if the date is the same, including the year. For example, if the date field is 1990-01-01 and the current date is
2023-01-01, the operator returns false. This operator is not suitable for a birthday campaign, as it will only include the customers who were born on the same day and year as the current date, which is very unlikely.
* B. The Is Birthday operator is not a valid operator in Data Cloud. There is no such operator available in the segment canvas or the calculated insight editor.
* C. The Is Between operator compares a date field with a range of dates and returns true if the date is within the range, including the endpoints. For example, if the date field is1990-01-01 and the range is
2022-12-25 to 2023-01-05, the operator returns true. This operator is not suitable for a birthday campaign, as it will only include the customers who have their birthday within a fixed range of dates, and the segment will not be updated daily with the new birthdays.
質問 # 105
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 the file exists in the specified bucket location.
- B. Check if the Amazon S3 data source is enabled in Data Cloud Setup.
- C. Check if correct permissions are configured for the S3 user.
- D. Check if correct permissions are configured for the Data Cloud user.
正解：A、D
解説：
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
質問 # 106
Which two common use cases can be addressed with Data Cloud?
Choose 2 answers
- A. Harmonize data from multiple sources with a standardized and extendable data model.
- B. Understand and act upon customer data to drive more relevant experiences.
- C. Safeguard critical business data by serving as a centralized system for backup and disaster recovery.
- D. Govern enterprise data lifecycle through a centralized set of policies and processes.
正解：A、B
解説：
Explanation
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the common use cases that can be addressed with Data Cloud are:
* Understand and act upon customer data to drive more relevant experiences. Data Cloud can help customers gain a 360-degree view of their customers by unifying data from different sources and resolving identities across channels. Data Cloud can also help customers segment their audiences, create personalized experiences, and activate data in any channel using insights and AI.
* Harmonize data from multiple sources with a standardized and extendable data model. Data Cloud can help customers transform and cleanse their data before using it, and map it to a common data model that can be extended and customized. Data Cloud can also help customers create calculated insights and related attributes to enrich their data and optimize identity resolution.
The other two options are not common use cases for Data Cloud. Data Cloud does not provide data governance or backup and disaster recovery features, as these are typically handled by other Salesforce or external solutions.
References:
* Learn How Data Cloud Works
* About Salesforce Data Cloud
* Discover Use Cases for the Platform
* Understand Common Data Analysis Use Cases
質問 # 107
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. Loyalty Management
- B. MobilePush
- C. Personalization
- D. MobileConnect
正解：B、D
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. Reference: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud
質問 # 108
If a data source does not have a field that can be designated as a primary key, what should the consultant do?
- A. Select a field as a primary key and then add a key qualifier.
- B. Use the default primary key recommended by Data Cloud.
- C. Remove duplicates from the data source and then select a primary key.
- D. Create a composite key by combining two or more source fields through a formula field.
正解：D
解説：
* Understanding Primary Keys in Salesforce Data Cloud:
A primary key is a unique identifier for records in a data source. It ensures that each record can be uniquely identified and accessed.
Reference:
* Challenges with Missing Primary Keys:
Some data sources may lack a natural primary key, making it difficult to uniquely identify records.
* Solution: Creating a Composite Key:
Composite Key Definition: A composite key is created by combining two or more fields to generate a unique identifier.
Formula Fields: Using a formula field, different fields can be concatenated to create a unique composite key.
Example: If "Email" and "Phone Number" together uniquely identify a record, a formula field can concatenate these values to form a composite key.
* Steps to Create a Composite Key:
Identify fields that, when combined, can uniquely identify each record.
Create a formula field that concatenates these fields.
Use this composite key as the primary key for the data source in Data Cloud.
質問 # 109
How does identity resolution select attributes for unified individuals when there Is conflicting information in the data model?
- A. Leverages reconciliation rules
- B. Creates additional rulesets
- C. Creates additional contact points
- D. Leverages match rules
正解：A
解説：
Identity resolution is the process of creating unified profiles of individuals by matching and merging data from different sources. When there is conflicting information in the data model, such as different names, addresses, or phone numbers for the same person, identity resolution leverages reconciliation rules to select the most accurate and complete attributes for the unified profile. Reconciliation rules are configurable rules that define how to resolve conflicts based on criteria such as recency, frequency, source priority, or completeness. For example, a reconciliation rule can specify that the most recent name or the most frequent phone number should be selected for the unified profile. Reconciliation rules can be applied at the attribute level or the contact point level. Reference: Identity Resolution, Reconciliation Rules, Salesforce Data Cloud Exam Questions
質問 # 110
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?
- A. Streaming insight
- B. Batch transforms
- C. Segmentation exclude rules
- D. Related attributes
正解：C
解説：
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign.
The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules
質問 # 111
Northern Trail Outfitters (NTO) wants to send a promotional campaign for customers that have purchased within the past 6 months. The consultant created a segment to meet this requirement.
Now, NTO brings an additional requirement to suppress customers who have made purchases within the last week.
What should the consultant use to remove the recent customers?
- A. Streaming insight
- B. Batch transforms
- C. Segmentation exclude rules
- D. Related attributes
正解：C
解説：
Explanation
The consultant should use B. Segmentation exclude rules to remove the recent customers. Segmentation exclude rules are filters that can be applied to a segment to exclude records that meet certain criteria. The consultant can use segmentation exclude rules to exclude customers who have made purchases within the last week from the segment that contains customers who have purchased within the past 6 months. This way, the segment will only include customers who are eligible for the promotional campaign.
The other options are not correct. Option A is incorrect because batch transforms are data processing tasks that can be applied to data streams or data lake objects to modify or enrich the data. Batch transforms are not used for segmentation or activation. Option C is incorrect because related attributes are attributes that are derived from the relationships between data model objects. Related attributes are not used for excluding records from a segment. Option D is incorrect because streaming insights are derived attributes that are calculated at the time of data ingestion. Streaming insights are not used for excluding records from a segment. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Segmentation Exclude Rules
質問 # 112
Northern Trail Outfitters (NTO), an outdoor lifestyle clothing brand, recently started a new line of business. The new business specializes in gourmet camping food. For business reasons as well as security reasons, it's important to NTO to keep all Data Cloud data separated by brand.
Which capability best supports NTO's desire to separate its data by brand?
- A. Data spaces for each brand
- B. Data streams for each brand
- C. Data sources for each brand
- D. Data model objects for each brand
正解：A
解説：
Data spaces are logical containers that allow you to separate and organize your data by different criteria, such as brand, region, product, or business unit1. Data spaces can help you manage data access, security, and governance, as well as enable cross-cloud data integration and activation2. For NTO, data spaces can support their desire to separate their data by brand, so that they can have different data models, rules, and insights for their outdoor lifestyle clothing and gourmet camping food businesses. Data spaces can also help NTO comply with any data privacy and security regulations that may apply to their different brands3. The other options are incorrect because they do not provide the same level of data separation and organization as data spaces. Data streams are used to ingest data from different sources into Data Cloud, but they do not separate the data by brand4. Data model objects are used to define the structure and attributes of the data, but they do not isolate the data by brand5. Data sources are used to identify the origin and type of the data, but they do not partition the data by brand. Reference: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]
質問 # 113
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations.
Which configuration change should a consultant consider in order to increase the consolidation rate?
- A. Reduce the number of matching rules.
- B. Change reconciliation rules to Most Occurring.
- C. Include additional attributes in the existing matching rules.
- D. Increase the number of matching rules.
正解：D
質問 # 114
During an implementation project, a consultant completed ingestion of all data streams for their customer.
Prior to segmenting and acting on that data, which additional configuration is required?
- A. Data Activation
- B. Calculated Insights
- C. Identity Resolution
- D. Data Mapping
正解：C
解説：
After ingesting data from different sources into Data Cloud, the additional configuration that is required before segmenting and acting on that data is Identity Resolution. Identity Resolution is the process of matching and reconciling source profiles from different data sources and creating unified profiles that represent a single individual or entity1. Identity Resolution enables you to create a 360-degree view of your customers and prospects, and to segment and activate them based on their attributes and behaviors2. To configure Identity Resolution, you need to create and deploy a ruleset that defines the match rules and reconciliation rules for your data3. The other options are incorrect because they are not required before segmenting and acting on the data. Data Activation is the process of sending data from Data Cloud to other Salesforce clouds or external destinations for marketing, sales, or service purposes4. Calculated Insights are derived attributes that are computed based on the source or unified data, such as lifetime value, churn risk, or product affinity5. Data Mapping is the process of mapping source attributes to unified attributes in the data model. These configurations can be done after segmenting and acting on the data, or in parallel with Identity Resolution, but they are not prerequisites for it. Reference: Identity Resolution Overview, Segment and Activate Data in Data Cloud, Configure Identity Resolution Rulesets, Data Activation Overview, Calculated Insights Overview, [Data Mapping Overview]
質問 # 115
A consultant at Northern Trail Outfitters is attempting to ingest a field from the Contact object in Salesforce CRM that contains both yyyy-mm-dd and yyyy-mm-dd hh:mm:ss values. The target field is set to Date datatype.
Which statement is true in this situation?
- A. The target field will only hold the time part and ignore the date part.
- B. The target field will be able to hold both types of values.
- C. The target field will throw an error and store null values.
- D. The target field will only hold the date part and ignore the time part.
正解：D
解説：
* Field Data Types: Salesforce CRM's Contact object fields can store data in various formats. When ingesting data into Salesforce Data Cloud, the target field's data type determines how the data is processed and stored.
* Date Data Type: If the target field in Data Cloud is set to Date data type, it is designed to store date values without time information.
* Mixed Format Values: When ingesting a field containing both date (yyyy-mm-dd) and datetime (yyyy-mm-dd hh:mm:ss) values into a Date data type field:
The Date field will extract and store only the date part (yyyy-mm-dd), ignoring the time part (hh:mm:ss).
* Result:
Date Values: yyyy-mm-dd values are stored as-is.
Datetime Values: yyyy-mm-dd hh:mm:ss values are truncated to yyyy-mm-dd, and the time component is ignored.
* Reference:
Salesforce Data Cloud Field Mapping
Salesforce Data Types
質問 # 116
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 Zonesetting.
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. The team member in the Eastern time zone.
- B. The team member in the Pacific time zone.
- C. Both team members; Data Cloud adjusts the segment and activation schedules to the time zone of the logged-in user
- D. Neither team member; Data Cloud showsall schedules in GMT.
正解：C
解説：
Explanation
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. References:
* 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 # 117
What does it mean to build a trust-based, first-party data asset?
- A. To provide trusted, first-party data in the Data Cloud Marketplace that follows all compliance regulations
- B. To provide transparency and security for data gathered from individuals who provide consent for its use and receive value in exchange
- C. To ensure opt-in consents are collected for all email marketing as required by law
- D. To obtain competitive data from reliable sources through interviews, surveys, and polls
正解：B
解説：
Building a trust-based, first-party data asset means collecting, managing, and activating data from your own customers and prospects in a way that respects their privacy and preferences. It also means providing them with clear and honest information about how you use their data, what benefits they can expect from sharing their data, and how they can control their data. By doing so, you can create a mutually beneficial relationship with your customers, where they trust you to use their data responsibly and ethically, and you can deliver more relevant and personalized experiences to them. A trust-based, first-party data asset can help you improve customer loyalty, retention, and growth, as well as comply with data protection regulations and standards. Reference: Use first-party data for a powerful digital experience, Why first-party data is the key to data privacy, Build a first-party data strategy
質問 # 118
A customer requests that their personal data be deleted.
Which action should the consultant take to accommodate this request in Data Cloud?
- A. Use the Data Rights Subject Request tool to request deletion of the customer's information.
- B. Use a streaming API call to delete the customer's information.
- C. Use Consent API to request deletion of the customer's information.
- D. Use Profile Explorer to delete the customer data from Data Cloud.
正解：A
解説：
Explanation
The Data Rights Subject Request tool is a feature that allows Data Cloud users to manage customer requests for data access, deletion, or portability. The tool provides a user interface and an API to create, track, and fulfill data rights requests. The tool also generates a report that contains the customer's personal data and the actions taken to comply with the request. The consultant should use this tool to accommodate the customer's request for data deletion in Data Cloud. References: Data Rights Subject Request Tool, Create a Data Rights Subject Request
質問 # 119
What is a typical use case for Salesforce Data Cloud?
- A. Data synchronization across the Salesforce ecosystem
- B. Storing CRM data on promises
- C. Data harmonization across multiple platforms
- D. Sending personalized emails at scale
正解：C
質問 # 120
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