Salesforce Salesforce Data CloudAccredited Professional Exam (SU24) Salesforce-Data-Cloud Exam Dumps: Updated Questions & Answers (January 2026)

The data model subject area that should be used for any Organization, Individual, or Member in the Customer 360 data model is the Party subject area. The Party subject area defines the entities that are involved in any business transaction or relationship, such as customers, prospects, partners, suppliers, etc. The Party subject area contains the following data model objects (DMOs):

Organization: A DMO that represents a legal entity or a business unit, such as a company, a department, a branch, etc.

Individual: A DMO that represents a person, such as a customer, a contact, a user, etc.

Member: A DMO that represents the relationship between an individual and an organization, such as an employee, a customer, a partner, etc.

The other options are not data model subject areas that should be used for any Organization, Individual, or Member in the Customer 360 data model. The Engagement subject area defines the actions that people take, such as clicks, views, purchases, etc. The Membership subject area defines the associations that people have with groups, such as loyalty programs, clubs, communities, etc. The Global Account subject area defines the hierarchical relationships between organizations, such as parent-child, subsidiary, etc.

Data Model Subject Areas

Party Subject Area

Customer 360 Data Model

The correct answer is C, the desired attributes reside on different related paths. When creating an activation in Data Cloud, you can select related attributes from data model objects that are linked to the segment entity. However, not all related attributes are available for every activation. The availability of related attributes depends on the container path, which is the sequence of data model objects that connects the segment entity to the related entity. For example, if you segment on the Unified Individual entity, you can select related attributes from the Order Product entity, but only if the container path is Unified Individual > Order > Order Product. If the container path is Unified Individual > Order Line Item > Order Product, then the related attributes from Order Product are not available for activation. This is because Data Cloud only supports one-to-many relationships for related attributes, and Order Line Item is a many-to-many junction object between Order and Order Product. Therefore, you need to ensure that the desired attributes reside on the same related path as the segment entity, and that the path does not include any many-to-many junction objects. The other options are incorrect because they do not explain why the related attributes are not available. The segment entity can be any data model object, not just profile data. The attributes are not restricted by being used in another activation. Activations can include one-to-many attributes, not just one-to-one attributes. References:

Related Attributes in Activation

Considerations for Selecting Related Attributes

Salesforce Launches: Data Cloud Consultant Certification

Create a Segment in Data Cloud

Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency. Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. References: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.

Data Lake Objects (DLOs) and Data Model Objects (DMOs): In Salesforce Data Cloud, DLOs are mapped to DMOs to organize and structure data. Categories like Profile, Engagement, and Other define how these mappings are used.

Engagement Category: Mapping a DLO to the Engagement category indicates that the data is related to customer interactions and activities.

Impact on Future Mappings:

Engagement Category Restriction: When a DLO like Order-Headers is mapped to the Sales Order DMO under the Engagement category, future mappings of the Sales Order DMO are restricted to Engagement category DLOs.

Category Assignment: The Sales Order DMO is assigned to the Engagement category, meaning only DLOs categorized as Engagement can be mapped to it in the future.

Benefits:

Consistency: Ensures consistent data categorization and usage, aligning data with its intended purpose.

Accuracy: Helps in maintaining the integrity of data mapping and ensures that engagement-related data is accurately captured and utilized.

References:

Salesforce Data Cloud Mapping

Salesforce Data Cloud Categories

 The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space. Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations.

The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud.

Marketing Cloud Data Extension Data Stream

Data Cloud Data Ingestion

[Marketing Cloud Data Extension Data Stream API]

[Marketing Cloud Connect API]

[Email Studio Starter Data Bundle]

When advising a customer about using the Consent API in Salesforce to comply with requests for the right to be forgotten, the consultant should focus on two primary considerations:

Data deletion requests are submitted for Individual profiles (Answer C): The Consent API in Salesforce is designed to handle data deletion requests specifically for individual profiles. This means that when a request is made to delete data, it is targeted at the personal data associated with an individual's profile in the Salesforce system. The consultant should inform the customer that the requests must be specific to individual profiles to ensure accurate processing and compliance with privacy laws.

Data deletion requests submitted to Data Cloud are passed to all connected Salesforce clouds (Answer D): When a data deletion request is made through the Consent API in Salesforce Data Cloud, the request is not limited to the Data Cloud alone. Instead, it propagates through all connected Salesforce clouds, such as Sales Cloud, Service Cloud, Marketing Cloud, etc. This ensures comprehensive compliance with the right to be forgotten across the entire Salesforce ecosystem. The customer should be aware that the deletion request will affect all instances of the individual’s data across the connected Salesforce environments.

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. References: Data Spaces Overview, Create Data Spaces, Data Privacy and Security in Data Cloud, Data Streams Overview, Data Model Objects Overview, [Data Sources Overview]

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 :

A. Data synchronization across the Salesforce ecosystem : While Data Cloud integrates with Salesforce products, its primary focus is on unifying data from multiple platforms, not just Salesforce.

B. Storing CRM data on premises : Data Cloud is a cloud-based solution and does not support on-premises storage.

D. Sending personalized emails at scale : This is a use case for Marketing Cloud, not Data Cloud.

Steps to Achieve Data Harmonization

Step 1: Ingest Data

Bring in customer data from multiple sources (e.g., CRM, Marketing Cloud, external systems) into Data Cloud.

Step 2: Standardize and Cleanse Data

Use batch or streaming transformations to standardize formats, remove duplicates, and cleanse data.

Step 3: Create Unified Profiles

Use identity resolution to merge related records into a single unified profile.

Step 4: Activate Insights

Leverage the harmonized data for segmentation, personalization, and analytics.

Conclusion

The most typical use case for Salesforce Data Cloud is data harmonization across multiple platforms , enabling organizations to unify and leverage customer data effectively.

The Data Cloud User permission set is the minimum permission set needed to accommodate this use case. The Data Cloud User permission set grants access to the Data Explorer feature, which allows the user to review individual rows of ingested data and validate that it has been modeled successfully to its linked data model object. The user can also make changes to the data model object fields, such as adding or removing fields, changing field types, or creating formula fields. The Data Cloud User permission set does not grant access to other Data Cloud features or tasks, such as creating data streams, creating segments, creating activations, or managing users. The other permission sets are either too restrictive or too permissive for this use case. The Data Cloud for Marketing Specialist permission set only grants access to the segmentation and activation features, but not to the Data Explorer feature. The Data Cloud Admin permission set grants access to all Data Cloud features and tasks, including the Data Explorer feature, but it is more than what the user needs. The Data Cloud for Marketing Data Aware Specialist permission set grants access to the Data Explorer feature, but also to the segmentation and activation features, which are not required for this use case. References: Data Cloud Standard Permission Sets, Data Explorer, Set Up Data Cloud Unit

Understanding the Use Case:

The leadership team wants to focus on customers who have deposited more than $250,000 in the last five years and are not using advisory services.