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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Data 360 Consultant |
| Exam Number: | Data-Con-101 |
| Passing Score: | 63% |
| Exam Price: | $200 USD |
| Exam Format: | Multiple Choice, Multiple Select |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 60 |
| Related Certifications: | Salesforce Certified Administrator Salesforce Certified Data Architect |
| Sample Questions: | Salesforce Data-Cloud-Consultant Sample Questions |
| Exam Way: | Online proctored exam |
| Pre Condition: | Recommended: Salesforce Administrator certification and hands-on experience with Data Cloud implementation |
| Official Syllabus URL: | https://trailhead.salesforce.com/credentials/data360consultant |
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NEW QUESTION # 24
Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?
Answer: B
Explanation:
Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the data spaces feature and apply filtering on the Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries. Reference: Data Spaces, Create a Data Space
NEW QUESTION # 25
A customer notices that their consolidation rate is low across their account unification. They have mapped Account to the Individual and Contact Point Email DMOs.
What should they do to increase their consolidation rate?
Answer: D
Explanation:
Consolidation Rate: The consolidation rate in Salesforce Data Cloud refers to the effectiveness of unifying records into a single profile. A low consolidation rate indicates that many records are not being successfully unified.
Matching Rules: Matching rules are critical in the identity resolution process. They define the criteria for identifying and merging duplicate records.
Solution:
* Increase Matching Rules: Adding more matching rules improves the system's ability to identify duplicate records. This includes matching on additional fields or using more sophisticated matching algorithms.
* Steps:
* Access the Identity Resolution settings in Data Cloud.
* Review the current matching rules.
* Add new rules that consider more fields such as phone number, address, or other unique identifiers.
Benefits:
* Improved Unification: Higher accuracy in matching and merging records, leading to a higher consolidation rate.
* Comprehensive Profiles: Enhanced customer profiles with consolidated data from multiple sources.
References:
* Salesforce Data Cloud Identity Resolution
* Salesforce Help: Matching Rules
NEW QUESTION # 26
A consultant is preparing to implement Data Cloud.
Which ethic should the consultant adhere to regarding customer data?
Answer: C
Explanation:
When implementing Data Cloud, the consultant should adhere to ethical practices regarding customer data, particularly by carefully considering the collection and use of sensitive data such as age, gender, or ethnicity . Here's why:
Understanding Ethical Considerations
Collecting and using customer data comes with significant ethical responsibilities, especially when dealing with sensitive information.
The consultant must ensure compliance with privacy regulations (e.g., GDPR, CCPA) and uphold ethical standards to protect customer trust.
Why Carefully Consider Sensitive Data?
Privacy and Trust :
Collecting sensitive data (e.g., age, gender, ethnicity) can raise privacy concerns and erode customer trust if not handled appropriately.
Customers are increasingly aware of their data rights and expect transparency and accountability.
Regulatory Compliance :
Regulations like GDPR and CCPA impose strict requirements on the collection, storage, and use of sensitive data.
Careful consideration ensures compliance and avoids potential legal issues.
Other Options Are Less Suitable :
A . Allow senior leaders in the firm to access customer data for audit purposes : While audits are important, unrestricted access to sensitive data is unethical and violates privacy principles.
B . Collect and use all of the data to create more personalized experiences : Collecting all data without regard for sensitivity is unethical and risks violating privacy regulations.
C . Map sensitive data to the same DMO for ease of deletion : While mapping data for deletion is a good practice, it does not address the ethical considerations of collecting sensitive data in the first place.
Steps to Ensure Ethical Practices
Step 1: Evaluate Necessity
Assess whether sensitive data is truly necessary for achieving business objectives.
Step 2: Obtain Explicit Consent
If sensitive data is required, obtain explicit consent from customers and provide clear explanations of how the data will be used.
Step 3: Minimize Data Collection
Limit the collection of sensitive data to only what is essential and anonymize or pseudonymize data where possible.
Step 4: Implement Security Measures
Use encryption, access controls, and other security measures to protect sensitive data.
Conclusion
The consultant should carefully consider asking for sensitive data such as age, gender, or ethnicity to uphold ethical standards, maintain customer trust, and ensure regulatory compliance.
NEW QUESTION # 27
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?
Answer: C
Explanation:
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can be reused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
Reference:
Create a Container Block
Create a Segment in Data Cloud
Create and Publish a Data Kit
Create a Nested Segment
NEW QUESTION # 28
A customer has a custom Customer Email c object related to the standard Contact object in Salesforce CRM.
This custom object
stores the email address a Contact that they want to use for activation.
To which data entity is mapped?
Answer: B
Explanation:
The Contact Point_Email object is the data entity that represents an email address associated with an individual in Data Cloud. It is part of the Customer 360 Data Model, which is a standardized data model that defines common entities and relationships for customer data. The Contact Point_Email object can be mapped to any custom or standard object that stores email addresses in Salesforce CRM, such as the custom Customer Email__c object. The other options are not the correct data entities to map to because:
* A. The Contact object is the data entity that represents a person who is associated with an account that is
* a customer, partner, or competitor in Salesforce CRM. It is not the data entity that represents an email address in Data Cloud.
* C. The custom Customer Email__c object is not a data entity in Data Cloud, but a custom object in Salesforce CRM. It can be mapped to a data entity in Data Cloud, such as the Contact Point_Email object, but it is not a data entity itself.
* D. The Individual object is the data entity that represents a unique person in Data Cloud. It is the core entity for managing consent and privacy preferences, and it can be related to one or more contact points, such as email addresses, phone numbers, or social media handles. It is not the data entity that represents an email address in Data Cloud. References: Customer 360 Data Model: Individual and Contact Points - Salesforce, Contact Point_Email | Object Reference for the Salesforce Platform | Salesforce Developers,
[Contact | Object Reference for the Salesforce Platform | Salesforce Developers], [Individual | Object Reference for the Salesforce Platform | Salesforce Developers]
NEW QUESTION # 29
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