Salesforce Data Cloud Consultant Practice Exams
Last updated on Sep 13,2026- Exam Code: Data Cloud Consultant
- Exam Name: Salesforce Certified Data Cloud Consultant
- Certification Provider: Salesforce
- Latest update: Sep 13,2026
Question #131
How does Data Cloud ensure data privacy and security?
- A . By encrypting data at rest and in transit
- B . By enforcing and controlling consent references
- C . By securely storing data in an offsite server
- D . BY limiting data access to authorized admins
Correct Answer: A
A
Explanation:
Data Privacy and Security in Data Cloud:
Ensuring data privacy and security is paramount in Salesforce Data Cloud.
Reference: Salesforce Data Privacy and Security Overview
Key Security Measures:
Encrypting Data at Rest and in Transit:
Data encryption ensures that information is protected from unauthorized access both when stored and when transmitted.
Reference: Salesforce Encryption Documentation
Enforcing and Controlling Consent Preferences:
Consent management ensures that data usage complies with customer permissions and regulatory requirements.
Reference: Salesforce Consent Management Guide
Steps to Implement Security Measures:
Data Encryption:
Enable encryption for data at rest using Salesforce Shield. Ensure TLS/SSL encryption is used for data in transit. Consent Management:
Set up and enforce consent preferences within Data Cloud.
Regularly audit and update consent records.
Reference: Salesforce Shield Encryption and Consent Management Implementation Guide Practical Application:
Example: A financial institution uses encryption to secure customer financial data and manages consent to comply with GDPR.
Reference: Salesforce Data Privacy Case Studies
A
Explanation:
Data Privacy and Security in Data Cloud:
Ensuring data privacy and security is paramount in Salesforce Data Cloud.
Reference: Salesforce Data Privacy and Security Overview
Key Security Measures:
Encrypting Data at Rest and in Transit:
Data encryption ensures that information is protected from unauthorized access both when stored and when transmitted.
Reference: Salesforce Encryption Documentation
Enforcing and Controlling Consent Preferences:
Consent management ensures that data usage complies with customer permissions and regulatory requirements.
Reference: Salesforce Consent Management Guide
Steps to Implement Security Measures:
Data Encryption:
Enable encryption for data at rest using Salesforce Shield. Ensure TLS/SSL encryption is used for data in transit. Consent Management:
Set up and enforce consent preferences within Data Cloud.
Regularly audit and update consent records.
Reference: Salesforce Shield Encryption and Consent Management Implementation Guide Practical Application:
Example: A financial institution uses encryption to secure customer financial data and manages consent to comply with GDPR.
Reference: Salesforce Data Privacy Case Studies
Question #132
Cumulus Financial segregates its sales CRM data based on Region for its Data Cloud users. Multiple
data spaces are configured: a default space and two additional spaces tailored for EMEA and APAC regions.
EME A sales reps who need temporary access to visualize data for both regions say that they cannot visualize APAC data. APAC sales reps can visualize the corresponding segmented data.
Which statement describes the cause of this issue?
- A . The EMEA sales reps have not been assigned to the profile associated with the APAC data space.
- B . The APAC data space is not associated with any permission set.
- C . The APAC data space Is not associated with any profile.
- D . The EMEA sales reps have not been assigned to the permission set associated with the APAC data space.
Correct Answer: D
D
Explanation:
The issue arises because the EMEA sales reps cannot visualize APAC data, while APAC sales reps can access their segmented data. The root cause is that the EMEA sales reps lack the necessary permissions to access the APAC data space.
Here’s why:
Understanding the Issue
Cumulus Financial uses data spaces to segregate CRM data by region (default, EMEA, APAC).
EMEA sales reps need temporary access to APAC data but are unable to view it.
APAC sales reps can access their corresponding segmented data without issues.
Why Permission Sets?
Data Space Access Control:
Data spaces in Salesforce Data Cloud are secured using profiles and permission sets .
Users must be explicitly granted access to a data space via their assigned profiles or permission sets.
Root Cause Analysis:
Since APAC sales reps can access their data, the APAC data space is properly configured.
The issue lies with the EMEA sales reps, who likely do not have the required permission set granting
access to the APAC data space.
Temporary Access:
Temporary access can be granted by assigning the appropriate permission set to the EMEA sales reps.
Steps to Resolve the Issue
Step 1: Identify the Required Permission Set
Navigate to Setup > Permission Sets and locate the permission set associated with the APAC data space.
Step 2: Assign the Permission Set
Assign the APAC data space permission set to the EMEA sales reps requiring temporary access.
Step 3: Verify Access
Confirm that the EMEA sales reps can now visualize APAC data.
Step 4: Revoke Temporary Access
Once the temporary access period ends, remove the permission set from the EMEA sales reps.
Why Not Other Options?
D
Explanation:
The issue arises because the EMEA sales reps cannot visualize APAC data, while APAC sales reps can access their segmented data. The root cause is that the EMEA sales reps lack the necessary permissions to access the APAC data space.
Here’s why:
Understanding the Issue
Cumulus Financial uses data spaces to segregate CRM data by region (default, EMEA, APAC).
EMEA sales reps need temporary access to APAC data but are unable to view it.
APAC sales reps can access their corresponding segmented data without issues.
Why Permission Sets?
Data Space Access Control:
Data spaces in Salesforce Data Cloud are secured using profiles and permission sets .
Users must be explicitly granted access to a data space via their assigned profiles or permission sets.
Root Cause Analysis:
Since APAC sales reps can access their data, the APAC data space is properly configured.
The issue lies with the EMEA sales reps, who likely do not have the required permission set granting
access to the APAC data space.
Temporary Access:
Temporary access can be granted by assigning the appropriate permission set to the EMEA sales reps.
Steps to Resolve the Issue
Step 1: Identify the Required Permission Set
Navigate to Setup > Permission Sets and locate the permission set associated with the APAC data space.
Step 2: Assign the Permission Set
Assign the APAC data space permission set to the EMEA sales reps requiring temporary access.
Step 3: Verify Access
Confirm that the EMEA sales reps can now visualize APAC data.
Step 4: Revoke Temporary Access
Once the temporary access period ends, remove the permission set from the EMEA sales reps.
Why Not Other Options?
Question #133
Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unified view of its customers and all their order transactions.
What should the consultant keep in mind with regard to historical data ingesting order data using the B2C Commerce Order Bundle?
- A . The B2C Commerce Order Bundle ingests 12 months of historical data.
- B . The B2C Commerce Order Bundle ingests 6 months of historical data.
- C . The B2C Commerce Order Bundle does not ingest any historical data and only ingests new orders from that point on.
- D . The B2C Commerce Order Bundle ingests 30 days of historical data.
Correct Answer: C
C
Explanation:
The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file12.
Reference: Create a B2C Commerce Data Bundle
Data Access and Export for B2C Commerce and Commerce Marketplace
C
Explanation:
The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file12.
Reference: Create a B2C Commerce Data Bundle
Data Access and Export for B2C Commerce and Commerce Marketplace
Question #134
An analyst from Cloud Kicks needs to get quick Insights to determine the average sales per day during the past week.
What should a consultant recommend?
- A . salesforce flows
- B . Lightning web component utilizing Query API
- C . Salesforce reports
- D . Segment activation to Azure
Correct Answer: C
C
Explanation:
To help the analyst from Cloud Kicks determine the average sales per day during the past week, Salesforce Reports is the most efficient and straightforward solution. Here’s a detailed breakdown: Understanding Salesforce Reports:
Salesforce Reports is a native tool within the Salesforce platform that allows users to create, customize, and analyze data in various formats. It is particularly well-suited for quick insights and ad-hoc analysis without requiring complex development or integrations.
Why Not Other Options?
Option A (Salesforce Flows): While Salesforce Flows is a powerful automation tool, it is not designed for analytical purposes. Creating a flow to calculate average sales per day would require additional configuration and logic, making it unnecessarily complex for this use case.
Option B (Lightning Web Component Utilizing Query API): Using a Lightning Web Component with the Query API involves custom development. While this approach is flexible, it is overkill for a simple analytical task like calculating average sales.
Option D (Segment Activation to Azure): Segment activation refers to exporting segmented customer data to external platforms like Azure. This process is unrelated to generating quick insights and would introduce unnecessary complexity for this requirement.
How Salesforce Reports Can Be Used:
Step 1: Create a Report: Navigate to the Salesforce Reports tab and create a new report based on the relevant object (e.g., Opportunities or Orders).
Step 2: Filter by Date Range: Apply a filter to include only records from the past week. For example, set the "Close Date" field to "Last Week."
Step 3: Add Summary Fields: Use summary formulas or grouping to calculate total sales for each day. Then, compute the average sales per day by dividing the total sales by the number of days in the range.
Step 4: Run the Report: Execute the report to view the results instantly.
Salesforce Documentation Reference:
Salesforce’s official documentation highlights that Reports are the go-to tool for analyzing and summarizing data quickly. They are designed to provide actionable insights without requiring advanced technical skills, making them ideal for tasks like calculating average sales.
By leveraging Salesforce Reports, the analyst can efficiently obtain the required insights without additional development or integration efforts.
C
Explanation:
To help the analyst from Cloud Kicks determine the average sales per day during the past week, Salesforce Reports is the most efficient and straightforward solution. Here’s a detailed breakdown: Understanding Salesforce Reports:
Salesforce Reports is a native tool within the Salesforce platform that allows users to create, customize, and analyze data in various formats. It is particularly well-suited for quick insights and ad-hoc analysis without requiring complex development or integrations.
Why Not Other Options?
Option A (Salesforce Flows): While Salesforce Flows is a powerful automation tool, it is not designed for analytical purposes. Creating a flow to calculate average sales per day would require additional configuration and logic, making it unnecessarily complex for this use case.
Option B (Lightning Web Component Utilizing Query API): Using a Lightning Web Component with the Query API involves custom development. While this approach is flexible, it is overkill for a simple analytical task like calculating average sales.
Option D (Segment Activation to Azure): Segment activation refers to exporting segmented customer data to external platforms like Azure. This process is unrelated to generating quick insights and would introduce unnecessary complexity for this requirement.
How Salesforce Reports Can Be Used:
Step 1: Create a Report: Navigate to the Salesforce Reports tab and create a new report based on the relevant object (e.g., Opportunities or Orders).
Step 2: Filter by Date Range: Apply a filter to include only records from the past week. For example, set the "Close Date" field to "Last Week."
Step 3: Add Summary Fields: Use summary formulas or grouping to calculate total sales for each day. Then, compute the average sales per day by dividing the total sales by the number of days in the range.
Step 4: Run the Report: Execute the report to view the results instantly.
Salesforce Documentation Reference:
Salesforce’s official documentation highlights that Reports are the go-to tool for analyzing and summarizing data quickly. They are designed to provide actionable insights without requiring advanced technical skills, making them ideal for tasks like calculating average sales.
By leveraging Salesforce Reports, the analyst can efficiently obtain the required insights without additional development or integration efforts.
Question #135
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
Correct Answer: C
C
Explanation:
A typical use case for Salesforce Data Cloud is data harmonization across multiple platforms. Here’s why:
Understanding Salesforce Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources, including CRM, Marketing Cloud, external systems, and third-party platforms.
Its primary purpose is to provide a unified view of customer data for personalized experiences and actionable insights.
Why Data Harmonization Across Multiple Platforms?
Data Harmonization:
Data Cloud harmonizes data by standardizing and cleansing it from disparate sources.
This ensures consistency and accuracy across platforms, enabling organizations to create a single
source of truth for customer data.
Use Case Alignment:
Data harmonization is a core functionality of Data Cloud, making it the most relevant use case among the options provided.
Other Options Are Less Relevant:
C
Explanation:
A typical use case for Salesforce Data Cloud is data harmonization across multiple platforms. Here’s why:
Understanding Salesforce Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources, including CRM, Marketing Cloud, external systems, and third-party platforms.
Its primary purpose is to provide a unified view of customer data for personalized experiences and actionable insights.
Why Data Harmonization Across Multiple Platforms?
Data Harmonization:
Data Cloud harmonizes data by standardizing and cleansing it from disparate sources.
This ensures consistency and accuracy across platforms, enabling organizations to create a single
source of truth for customer data.
Use Case Alignment:
Data harmonization is a core functionality of Data Cloud, making it the most relevant use case among the options provided.
Other Options Are Less Relevant:
Question #136
Cumulus Financial created a segment called Multiple Investments that contains individuals who have invested in two or more mutual funds.
The company plans to send an email to this segment regarding a new mutual fund offering, and wants to personalize the email content with information about each customer’s current mutual fund investments.
How should the Data Cloud consultant configure this activation?
- A . Include Fund Type equal to "Mutual Fund" as a related attribute. Configure an activation based on the new segment with no additional attributes.
- B . Choose the Multiple Investments segment, choose the Email contact point, add related attribute Fund Name, and add related attribute filter for Fund Type equal to "Mutual Fund".
- C . Choose the Multiple Investments segment, choose the Email contact point, and add related attribute Fund Type.
- D . Include Fund Name and Fund Type by default for post processing in the target system.
Correct Answer: B
B
Explanation:
To personalize the email content with information about each customer’s current mutual fund investments, the Data Cloud consultant needs to add related attributes to the activation. Related attributes are additional data fields that can be sent along with the segment to the target system for personalization or analysis purposes. In this case, the consultant needs to add the Fund Name attribute, which contains the name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to “Mutual Fund” to ensure that only relevant data is sent.
The other options are not correct because:
B
Explanation:
To personalize the email content with information about each customer’s current mutual fund investments, the Data Cloud consultant needs to add related attributes to the activation. Related attributes are additional data fields that can be sent along with the segment to the target system for personalization or analysis purposes. In this case, the consultant needs to add the Fund Name attribute, which contains the name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to “Mutual Fund” to ensure that only relevant data is sent.
The other options are not correct because:
Question #137
A Data Cloud consultant is working with data that is clean and organized. However, the various schemas refer to a person by multiple names ― such as user; contact, and subscriber ― and need a standard mapping.
Which term describes the process of mapping these different schema points into a standard data model?
- A . Segment
- B . Harmonize
- C . Unify
- D . Transform
Correct Answer: B
B
Explanation:
Introduction to Data Harmonization:
Data harmonization is the process of bringing together data from different sources and making it consistent.
Reference: Salesforce Data Harmonization Overview
Mapping Different Schema Points:
In Data Cloud, different schemas may refer to the same entity using different names (e.g., user, contact, subscriber).
Harmonization involves standardizing these different terms into a single, consistent schema.
Reference: Salesforce Schema Mapping Guide
Process of Harmonization:
Identify Variations: Recognize the different names and fields referring to the same entity across schemas.
Standard Mapping: Create a standard data model and map the various schema points to this model.
Example: Mapping “user”, “contact”, and “subscriber” to a single standard entity like “Customer.”
Reference: Salesforce Data Model Harmonization Documentation Steps to Harmonize Data:
Define a standard data model.
Map the fields from different schemas to this standard model.
Ensure consistency across the data ecosystem.
Reference: Salesforce Data Harmonization Best Practices
B
Explanation:
Introduction to Data Harmonization:
Data harmonization is the process of bringing together data from different sources and making it consistent.
Reference: Salesforce Data Harmonization Overview
Mapping Different Schema Points:
In Data Cloud, different schemas may refer to the same entity using different names (e.g., user, contact, subscriber).
Harmonization involves standardizing these different terms into a single, consistent schema.
Reference: Salesforce Schema Mapping Guide
Process of Harmonization:
Identify Variations: Recognize the different names and fields referring to the same entity across schemas.
Standard Mapping: Create a standard data model and map the various schema points to this model.
Example: Mapping “user”, “contact”, and “subscriber” to a single standard entity like “Customer.”
Reference: Salesforce Data Model Harmonization Documentation Steps to Harmonize Data:
Define a standard data model.
Map the fields from different schemas to this standard model.
Ensure consistency across the data ecosystem.
Reference: Salesforce Data Harmonization Best Practices
Question #138
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 plans 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.
Correct Answer: B
B
Explanation:
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 is 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. This approach allows the consultant to use the streaming transforms feature of Data Cloud, which enables data manipulation and transformation at the time of ingestion, without requiring any additional processing or storage. Streaming transforms can be used to normalize the phone numbers from the Contact data stream, such as removing spaces, dashes, or parentheses, and adding country codes if needed. The normalized phone numbers can then be stored in a separate Phone DLO, which can have one row for each phone number type (work, home, mobile). The Phone DLO can then be mapped to the Contact Point Phone data map object, which is a standard object that represents a phone number associated with a contact point. This way, the consultant can ensure that all the phone numbers are available for activation, such as sending SMS messages or making calls to the customers.
The other options are not as efficient as option B.
Option A is incorrect because it does not normalize the phone numbers, which may cause issues with activation or identity resolution.
Option C is incorrect because it requires creating a calculated insight, which is an additional step that consumes more resources and time than streaming transforms.
Option D is incorrect because it requires creating formula fields in the Contact data stream, which may not be supported by the CRM Connector or may cause conflicts with the existing fields in the Contact object.
Reference: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Streaming Transforms, Contact Point Phone
B
Explanation:
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 is 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. This approach allows the consultant to use the streaming transforms feature of Data Cloud, which enables data manipulation and transformation at the time of ingestion, without requiring any additional processing or storage. Streaming transforms can be used to normalize the phone numbers from the Contact data stream, such as removing spaces, dashes, or parentheses, and adding country codes if needed. The normalized phone numbers can then be stored in a separate Phone DLO, which can have one row for each phone number type (work, home, mobile). The Phone DLO can then be mapped to the Contact Point Phone data map object, which is a standard object that represents a phone number associated with a contact point. This way, the consultant can ensure that all the phone numbers are available for activation, such as sending SMS messages or making calls to the customers.
The other options are not as efficient as option B.
Option A is incorrect because it does not normalize the phone numbers, which may cause issues with activation or identity resolution.
Option C is incorrect because it requires creating a calculated insight, which is an additional step that consumes more resources and time than streaming transforms.
Option D is incorrect because it requires creating formula fields in the Contact data stream, which may not be supported by the CRM Connector or may cause conflicts with the existing fields in the Contact object.
Reference: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Streaming Transforms, Contact Point Phone
Question #139
The Data Cloud admin at Northern Trail Outfitters (NTO) wants to be proactively and immediately informed via Slack and email if any of the data streams fail for any reason. If this happens, a case should also be triggered as part of NTO’s existing support and triage process, and reflected in its global monitoring dashboard.
What should a consultant recommend for these requirements?
- A . Data actions
- B . Data Cloud Query Editor
- C . Salesforce flows
- D . Salesforce reports and dashboards
Correct Answer: C
C
Explanation:
To meet the requirement of being proactively and immediately informed via Slack and email if any data streams fail, and to trigger a case as part of the support process, the best solution is to use Salesforce Flows. Here’s why and how this works: Understanding the Requirements:
The admin wants to be notified immediately via Slack and email when a data stream fails.
A case should also be created automatically to reflect the issue in the global monitoring dashboard.
This requires an automated process that integrates with both internal systems (e.g., Slack, email) and
external workflows (e.g., case creation).
Why Salesforce Flows?
Salesforce Flows are highly flexible and can automate complex business processes. They can monitor system events (e.g., data stream failures) and trigger actions like sending notifications or creating records.
Flows can integrate seamlessly with Slack and email using platform events and action elements.
They can also create cases programmatically and update dashboards for real-time monitoring.
Steps to Implement This Solution:
Step 1: Navigate to Setup > Process Automation > Flows and create a new flow.
Step 2: Configure a Platform Event Trigger or Record-Triggered Flow to listen for data stream failure events.
Step 3: Add an action element to send a notification to Slack using the Slack Integration feature.
Step 4: Add another action element to send an email alert using the Send Email action.
Step 5: Add a step to create a Case record with details about the failure. Use predefined fields to populate relevant information (e.g., error message, timestamp).
Step 6: Update the global monitoring dashboard to reflect the newly created case. This can be done by linking the case to a report or dashboard component.
Why Not Other Options?
C
Explanation:
To meet the requirement of being proactively and immediately informed via Slack and email if any data streams fail, and to trigger a case as part of the support process, the best solution is to use Salesforce Flows. Here’s why and how this works: Understanding the Requirements:
The admin wants to be notified immediately via Slack and email when a data stream fails.
A case should also be created automatically to reflect the issue in the global monitoring dashboard.
This requires an automated process that integrates with both internal systems (e.g., Slack, email) and
external workflows (e.g., case creation).
Why Salesforce Flows?
Salesforce Flows are highly flexible and can automate complex business processes. They can monitor system events (e.g., data stream failures) and trigger actions like sending notifications or creating records.
Flows can integrate seamlessly with Slack and email using platform events and action elements.
They can also create cases programmatically and update dashboards for real-time monitoring.
Steps to Implement This Solution:
Step 1: Navigate to Setup > Process Automation > Flows and create a new flow.
Step 2: Configure a Platform Event Trigger or Record-Triggered Flow to listen for data stream failure events.
Step 3: Add an action element to send a notification to Slack using the Slack Integration feature.
Step 4: Add another action element to send an email alert using the Send Email action.
Step 5: Add a step to create a Case record with details about the failure. Use predefined fields to populate relevant information (e.g., error message, timestamp).
Step 6: Update the global monitoring dashboard to reflect the newly created case. This can be done by linking the case to a report or dashboard component.
Why Not Other Options?
Question #140
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 . Identity Resolution
- B . Query APL
- C . Data Explorer
- D . Profile Explorer
- E . Data Actions
Correct Answer: A, C, D
A, C, D
Explanation:
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
A, C, D
Explanation:
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