Salesforce Data Cloud Consultant Practice Exams
Last updated on Oct 28,2026- Exam Code: Data Cloud Consultant
- Exam Name: Salesforce Certified Data Cloud Consultant
- Certification Provider: Salesforce
- Latest update: Oct 28,2026
Question #21
Which statement about Data Cloud’s Web and Mobile Application Connector is true?
- A . A standard schema containing event, profile, and transaction data is created at the time the connector is configured.
- B . The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.
- C . Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.
- D . The connector schema can be updated to delete an existing field.
Correct Answer: B
B
Explanation:
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the
TSE.
Reference: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream
B
Explanation:
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the
TSE.
Reference: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream
Question #22
A consultant is helping a beauty company ingest its profile data into Data Cloud. The company’s source data includes several fields, such as eye color, skin type, and hair color, that are not fields in the standard Individual data model object (DMO).
What should the consultant recommend to map this data to be used for both segmentation and identity resolution?
- A . Create a custom DMO from scratch that has all fields that are needed.
- B . Create a custom DMO with only the additional fields and map it to the standard Individual DMO.
- C . Create custom fields on the standard Individual DMO.
- D . Duplicate the standard Individual DMO and add the additional fields.
Correct Answer: C
C
Explanation:
The best option to map the data to be used for both segmentation and identity resolution is to create custom fields on the standard Individual DMO. This way, the consultant can leverage the existing fields and functionality of the Individual DMO, such as identity resolution rulesets, calculated insights, and data actions, while adding the additional fields that are specific to the beauty company’s data1. Creating a custom DMO from scratch or duplicating the standard Individual DMO would require more effort and maintenance, and might not be compatible with the existing features of Data Cloud. Creating a custom DMO with only the additional fields and mapping it to the standard Individual DMO would create unnecessary complexity and redundancy, and might not allow the use of the custom fields for identity resolution.
Reference: 1: Data Model Objects in Data Cloud
C
Explanation:
The best option to map the data to be used for both segmentation and identity resolution is to create custom fields on the standard Individual DMO. This way, the consultant can leverage the existing fields and functionality of the Individual DMO, such as identity resolution rulesets, calculated insights, and data actions, while adding the additional fields that are specific to the beauty company’s data1. Creating a custom DMO from scratch or duplicating the standard Individual DMO would require more effort and maintenance, and might not be compatible with the existing features of Data Cloud. Creating a custom DMO with only the additional fields and mapping it to the standard Individual DMO would create unnecessary complexity and redundancy, and might not allow the use of the custom fields for identity resolution.
Reference: 1: Data Model Objects in Data Cloud
Question #23
Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.
What should NTO use to achieve this?
- A . B2C Commerce Starter Bundles
- B . Direct Sales Order entity ingestion
- C . Direct Sales Product entity ingestion
- D . B2C Commerce Starter Bundles plus a custom extract
Correct Answer: D
D
Explanation:
The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because: A. B2C Commerce Starter Bundles only ingest the last 90 days of data by default.
B. Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion.
C. Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce
data, only data ingestion.
Reference: Create a B2C Commerce Data Bundle – Salesforce, B2C Commerce Connector – Salesforce, Salesforce B2C Commerce Pricing Plans & Costs
D
Explanation:
The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because: A. B2C Commerce Starter Bundles only ingest the last 90 days of data by default.
B. Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion.
C. Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce
data, only data ingestion.
Reference: Create a B2C Commerce Data Bundle – Salesforce, B2C Commerce Connector – Salesforce, Salesforce B2C Commerce Pricing Plans & Costs
Question #24
A consultant needs to minimize the difference between a Data Cloud segment population and Marketing Cloud data extension count to determine the true size of segments for campaign planning.
What should the consultant recommend to filter the segments by to accomplish this?
- A . User preferences for marketing outreach
- B . Geographical divisions
- C . Marketing Cloud Journeys
- D . Business units
Correct Answer: B
Question #25
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 the View All object permission is enabled in the source Salesforce CRM org.
- C . Confirm the Ingest Object permission is enabled in the Salesforce CRM org.
- D . Confirm that the Modify Object permission is enabled in the Data Cloud org.
Correct Answer: B
B
Explanation:
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.
Reference: Manage Access with Data Cloud Permission Sets
Object Permissions
B
Explanation:
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.
Reference: Manage Access with Data Cloud Permission Sets
Object Permissions
Question #26
Which two dependencies prevent a data stream from being deleted? Choose 2 answers
- A . The underlying data lake object is used in activation.
- B . The underlying data lake object is used in a data transform.
- C . The underlying data lake object is mapped to a data model object.
- D . The underlying data lake object is used in segmentation.
Correct Answer: B C
B C
Explanation:
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a
data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2. Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
Reference: 1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead
B C
Explanation:
To delete a data stream in Data Cloud, the underlying data lake object (DLO) must not have any dependencies or references to other objects or processes. The following two dependencies prevent a
data stream from being deleted1:
Data transform: This is a process that transforms the ingested data into a standardized format and structure for the data model. A data transform can use one or more DLOs as input or output. If a DLO is used in a data transform, it cannot be deleted until the data transform is removed or modified2. Data model object: This is an object that represents a type of entity or relationship in the data model. A data model object can be mapped to one or more DLOs to define its attributes and values. If a DLO is mapped to a data model object, it cannot be deleted until the mapping is removed or changed3.
Reference: 1: Delete a Data Stream article on Salesforce Help
2: [Data Transforms in Data Cloud] unit on Trailhead
3: [Data Model in Data Cloud] unit on Trailhead
Question #27
A customer has two Data Cloud orgs. A new configuration has been completed and tested for an Amazon S3 data stream and its mappings in one of the Data Cloud orgs.
What is recommended to package and promote this configuration to the customer’s second org?
- A . Use the Metadata API.
- B . Use the Salesforce CRM connector.
- C . Create a data kit.
- D . Package as an AppExchange application.
Correct Answer: C
C
Explanation:
Data Cloud Configuration Promotion: When managing configurations across multiple Salesforce Data Cloud orgs, it’s essential to use tools that ensure consistency and accuracy in the promotion process.
Data Kits: Salesforce Data Cloud allows users to package and promote configurations using data kits. These kits encapsulate data stream definitions, mappings, and other configuration elements into a portable format.
Process:
Create a data kit in the source org that includes the Amazon S3 data stream configuration and mappings.
Export the data kit from the source org.
Import the data kit into the target org, ensuring that all configurations are transferred accurately.
Advantages: Using data kits simplifies the migration process, reduces the risk of configuration errors, and ensures that all settings and mappings are consistently applied in the new org.
Reference: Salesforce Data Cloud Developer Guide
Salesforce Data Cloud Packaging
C
Explanation:
Data Cloud Configuration Promotion: When managing configurations across multiple Salesforce Data Cloud orgs, it’s essential to use tools that ensure consistency and accuracy in the promotion process.
Data Kits: Salesforce Data Cloud allows users to package and promote configurations using data kits. These kits encapsulate data stream definitions, mappings, and other configuration elements into a portable format.
Process:
Create a data kit in the source org that includes the Amazon S3 data stream configuration and mappings.
Export the data kit from the source org.
Import the data kit into the target org, ensuring that all configurations are transferred accurately.
Advantages: Using data kits simplifies the migration process, reduces the risk of configuration errors, and ensures that all settings and mappings are consistently applied in the new org.
Reference: Salesforce Data Cloud Developer Guide
Salesforce Data Cloud Packaging
Question #28
Which method should a consultant use when performing aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK?
- A . Batch transform
- B . Calculated insight
- C . Streaming insight
- D . Formula fields
Correct Answer: C
C
Explanation:
Streaming insight is a method that allows you to perform aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK. Streaming insight is a feature that enables you to create real-time metrics and insights based on streaming data from various sources, such as web, mobile, or IoT devices. Streaming insight allows you to define aggregation rules, such as count, sum, average, min, max, or percentile, and apply them to streaming data in time windows of 15 minutes. For example, you can use streaming insight to calculate the number of visitors, the average session duration, or the conversion rate for your website or app in 15-minute intervals. Streaming insight also allows you to visualize and explore the aggregated data in dashboards, charts, or tables.
Reference: Streaming Insight, Create Streaming Insights
C
Explanation:
Streaming insight is a method that allows you to perform aggregations in windows of 15 minutes on data collected via the Interaction SDK or Mobile SDK. Streaming insight is a feature that enables you to create real-time metrics and insights based on streaming data from various sources, such as web, mobile, or IoT devices. Streaming insight allows you to define aggregation rules, such as count, sum, average, min, max, or percentile, and apply them to streaming data in time windows of 15 minutes. For example, you can use streaming insight to calculate the number of visitors, the average session duration, or the conversion rate for your website or app in 15-minute intervals. Streaming insight also allows you to visualize and explore the aggregated data in dashboards, charts, or tables.
Reference: Streaming Insight, Create Streaming Insights
Question #29
A customer has a requirement to be able to view the last time each segment was published within their Data Cloud org.
Which two features should the consultant recommend to best address this requirement? Choose 2 answers
- A . Profile Explorer
- B . Calculated insight
- C . Dashboard
- D . Report
Correct Answer: C D
C D
Explanation:
: A customer who wants to view the last time each segment was published within their Data Cloud org can use the dashboard and report features to achieve this requirement. A dashboard is a visual representation of data that can show key metrics, trends, and comparisons. A report is a tabular or matrix view of data that can show details, summaries, and calculations. Both dashboard and report features allow the user to create, customize, and share data views based on their needs and preferences. To view the last time each segment was published, the user can create a dashboard or a report that shows the segment name, the publish date, and the publish status fields from the segment object. The user can also filter, sort, group, or chart the data by these fields to get more insights and analysis. The user can also schedule, refresh, or export the dashboard or report data as needed.
Reference: Dashboards, Reports
C D
Explanation:
: A customer who wants to view the last time each segment was published within their Data Cloud org can use the dashboard and report features to achieve this requirement. A dashboard is a visual representation of data that can show key metrics, trends, and comparisons. A report is a tabular or matrix view of data that can show details, summaries, and calculations. Both dashboard and report features allow the user to create, customize, and share data views based on their needs and preferences. To view the last time each segment was published, the user can create a dashboard or a report that shows the segment name, the publish date, and the publish status fields from the segment object. The user can also filter, sort, group, or chart the data by these fields to get more insights and analysis. The user can also schedule, refresh, or export the dashboard or report data as needed.
Reference: Dashboards, Reports
Question #30
Cumulus Financial wants to be able to track the daily transaction volume of each of its customers in real time and send out a notification as soon as it detects volume outside a customer’s normal range.
What should a consultant do to accommodate this request?
- A . Use a calculated insight paired with a flow.
- B . Use streaming data transform with a flow.
- C . Use a streaming insight paired with a data action
- D . Use streaming data transform combined with a data action.
Correct Answer: C
C
Explanation:
: A streaming insight is a type of insight that analyzes streaming data in real time and triggers actions based on predefined conditions. A data action is a type of action that executes a flow, a data action target, or a data action script when an insight is triggered. By using a streaming insight paired with a data action, a consultant can accommodate Cumulus Financial’s request to track the daily transaction volume of each customer and send out a notification when the volume is outside the normal range. A calculated insight is a type of insight that performs calculations on data in a data space and stores the results in a data extension. A streaming data transform is a type of data transform that applies transformations to streaming data in real time and stores the results in a data extension. A flow is a type of automation that executes a series of actions when triggered by an event, a schedule, or another flow. None of these options can achieve the same functionality as a streaming insight paired with a data action.
Reference: Use Insights in Data Cloud Unit, Streaming Insights and Data Actions Use Cases, Streaming Insights and Data Actions Limits and Behaviors
C
Explanation:
: A streaming insight is a type of insight that analyzes streaming data in real time and triggers actions based on predefined conditions. A data action is a type of action that executes a flow, a data action target, or a data action script when an insight is triggered. By using a streaming insight paired with a data action, a consultant can accommodate Cumulus Financial’s request to track the daily transaction volume of each customer and send out a notification when the volume is outside the normal range. A calculated insight is a type of insight that performs calculations on data in a data space and stores the results in a data extension. A streaming data transform is a type of data transform that applies transformations to streaming data in real time and stores the results in a data extension. A flow is a type of automation that executes a series of actions when triggered by an event, a schedule, or another flow. None of these options can achieve the same functionality as a streaming insight paired with a data action.
Reference: Use Insights in Data Cloud Unit, Streaming Insights and Data Actions Use Cases, Streaming Insights and Data Actions Limits and Behaviors