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A steadily rising competition has been noted in the tech field. Countless candidates around the globe aspire to be Salesforce Certified Data Cloud Consultant in this field. Salesforce Data-Cloud-Consultant stand out from the rest of the Salesforce professionals. Once you become Salesforce certified, a whole new scope opens up to you and you are immediately hired by reputed firms. Even though the Salesforce Certified Data Cloud Consultant boosts your career options, you have to pass the Data-Cloud-Consultant Exam. This Salesforce Certified Data Cloud Consultant exam serves to filter out the capable from incapable candidates.

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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

Topic
Details

Topic 1

Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.

Topic 2

Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.

Topic 3

Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.

Topic 4

Identity Resolution: It describes matching and how its rule sets are applied. Furthermore, it discusses reconciling data and its rule sets, the results of identity resolution, and use cases.

Topic 5

Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.

Salesforce Certified Data Cloud Consultant Sample Questions (Q31-Q36):

NEW QUESTION # 31
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

Answer: B,D

Explanation:
The Marketing Cloud Starter Data Bundles are predefined data bundles that allow you to easily ingest data from Marketing Cloud into Data Cloud1. The available datasets in Marketing Cloud Starter Data Bundles are Email, MobileConnect, and MobilePush2. These datasets contain engagement events and metrics from different Marketing Cloud channels, such as email, SMS, and push notifications2. By using these datasets, you can enrich your Data Cloud data model with Marketing Cloud data and create segments and activations based on your marketing campaigns and journeys1. The other options are incorrect because they are not available datasets in Marketing Cloud Starter Data Bundles. Option A is incorrect because Personalization is not a dataset, but a feature of Marketing Cloud that allows you to tailor your content and messages to your audience3. Option C is incorrect because Loyalty Management is not a dataset, but a product of Marketing Cloud that allows you to create and manage loyalty programs for your customers4. References: Marketing Cloud Starter Data Bundles in Data Cloud, Connect Your Data Sources, Personalization in Marketing Cloud, Loyalty Management in Marketing Cloud

NEW QUESTION # 32
A consultant is setting up Data Cloud for a multi-brand organization and is using data spaces to segregate its data for various brands.
While starting the mapping of a data stream, the consultant notices that they cannot map the object for one of the brands.
What should the consultant do to make the object available for a new data space?

A. Create a new data stream and map the second data stream to the data space.
B. Navigate to the Data Space tab and select the object to be included in the new data space.
C. Create a batch transform to split data between different data spaces.
D. Copy data from the default data space to a new DMO using the Data Copy feature and link this DMO to the new data space.

Answer: B

Explanation:
When setting up Data Cloud for a multi-brand organization, if a consultant cannot map an object for one of the brands during data stream setup, they should navigate to the Data Space tab and select the object to include it in the new data space. Here's why:
Understanding the Issue
The consultant is using data spaces to segregate data for different brands.
While mapping a data stream, they notice that an object is unavailable for one of the brands.
This indicates that the object has not been associated with the new data space.
Why Navigate to the Data Space Tab?
Data Spaces and Object Availability :
Objects must be explicitly added to a data space before they can be used in mappings or transformations within that space.
If an object is missing, it means it has not been included in the data space configuration.
Solution Approach :
By navigating to the Data Space tab , the consultant can add the required object to the new data space.
This ensures the object becomes available for mapping and use in the data stream.
Steps to Resolve the Issue
Step 1: Navigate to the Data Space Tab
Go to Data Cloud > Data Spaces and locate the new data space for the brand.
Step 2: Add the Missing Object
Select the data space and click on Edit .
Add the required object (e.g., a Data Model Object or Data Lake Object) to the data space.
Step 3: Save and Verify
Save the changes and return to the data stream setup.
Verify that the object is now available for mapping.
Step 4: Complete the Mapping
Proceed with mapping the object in the data stream.
Why Not Other Options?
A . Create a new data stream and map the second data stream to the data space :
Creating a new data stream is unnecessary if the issue is simply object availability in the data space.
B . Copy data from the default data space to a new DMO using the Data Copy feature and link this DMO to the new data space :
This is overly complex and not required if the object can simply be added to the data space.
C . Create a batch transform to split data between different data spaces :
Batch transforms are used for data processing, not for resolving object availability issues.
Conclusion
The correct solution is to navigate to the Data Space tab and select the object to include it in the new data space . This ensures the object is available for mapping and resolves the issue efficiently.

NEW QUESTION # 33
Cumulus Financial offers both business and personal loans. Records in the Contact DLO can be useful for both groups since individual customers may have both business and personal loans. However, for legal reasons, the two groups must be kept separate.
How should Cumulus Financial solve this business requirement?

A. Duplicate the Contact DLO.
B. Use two data spaces.
C. Duplicate the Individual DM0.
D. Create two identity resolution rules in the same data space.

Answer: B

Explanation:
To address the business requirement where Cumulus Financial needs to keep business and personal loan records separate for legal reasons while still leveraging the same Contact DLO, the best solution is to use two data spaces . Here's why and how this works:
Understanding Data Spaces in Salesforce Data Cloud :Data spaces are logical containers within Salesforce Data Cloud that allow organizations to segment their data based on specific business needs, compliance requirements, or privacy regulations. They enable isolation of data processing and identity resolution rules while still allowing access to shared data objects like the Contact DLO.
Why Two Data Spaces?
By creating two data spaces (e.g., one for business loans and another for personal loans), Cumulus Financial can maintain separation between the two groups for legal compliance.
Both data spaces can reference the same Contact DLO, ensuring that individual customer data is not duplicated but is accessible in both contexts.
Identity resolution rules can be configured independently within each data space to ensure that the segmentation aligns with the legal requirements.
Steps to Implement This Solution :
Step 1: Navigate to the Data Spaces section in Salesforce Data Cloud.
Step 2: Create two new data spaces: one for "Business Loans" and another for "Personal Loans." Step 3: Configure the identity resolution rules separately for each data space to ensure proper segmentation.
Step 4: Link the existing Contact DLO to both data spaces. This ensures that the same contact data is available in both contexts without duplication.
Step 5: Set up activation rules and permissions to ensure that data from one data space cannot inadvertently mix with the other.
Why Not Other Options?
A). Duplicate the Individual DMO: This would lead to unnecessary duplication of data and increase storage costs. It also introduces complexity in maintaining consistency across duplicated records.
B). Duplicate the Contact DLO: Similar to duplicating the DMO, this approach increases storage and maintenance overhead without solving the core issue of legal separation.
C). Create two identity resolution rules in the same data space: While this might seem like a viable option, it does not provide the required legal separation since both groups would still exist within the same data space.
By using two data spaces, Cumulus Financial achieves the necessary legal separation while maintaining efficiency and avoiding data redundancy.

NEW QUESTION # 34
What should an organization use to stream inventory levels from an inventory management system into Data Cloud in a fast and scalable, near-real-time way?

A. Ingestion API
B. Marketing Cloud Personalization Connector
C. Commerce Cloud Connector
D. Cloud Storage Connector

Answer: A

Explanation:
Explanation
The Ingestion API is a RESTful API that allows you to stream data from any source into Data Cloud in a fast and scalable way. You can use the Ingestion API to send data from your inventory management system into Data Cloud as JSON objects, and then use Data Cloud to create data models, segments, and insights based on your inventory data. The Ingestion API supports both batch and streaming modes, and can handle up to
100,000 records per second. The Ingestion API also provides features such as data validation, encryption, compression, and retry mechanisms to ensure data quality and security. References: Ingestion API Developer Guide, Ingest Data into Data Cloud

NEW QUESTION # 35
A consultant notices that the unified individual profile is not storing the latest email address.
Which action should the consultant take to troubleshoot this issue?

A. Check if the mapping of DLO objects is correct to Contact Point Email.
B. Verify and update the email address in the source systems if needed.
C. Remove any old email addresses from Salesforce CRM.
D. Confirm that the reconciliation rules are correctly used.

Answer: D

Explanation:
Understanding Unified Individual Profile:
* The unified individual profile combines data from multiple sources to create a comprehensive view of each customer.

NEW QUESTION # 36
......

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Fred Shaw Fred Shaw

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