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100% Pass Quiz 2025 Fantastic Salesforce Data-Cloud-Consultant: Salesforce Certified Data Cloud Consultant Test Braindumps
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| 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.
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| Topic 2 |
- 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.
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| Topic 3 |
- Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
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| 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.
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Salesforce Certified Data Cloud Consultant Sample Questions (Q125-Q130):
NEW QUESTION # 125
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. Unify
- B. Transform
- C. Harmonize
- D. Segment
Answer: C
Explanation:
Introduction to Data Harmonization:
* Data harmonization is the process of bringing together data from different sources and making it consistent.
NEW QUESTION # 126
Which two common use cases can be addressed with Data Cloud?
Choose 2 answers
- A. Govern enterprise data lifecycle through a centralized set of policies and processes.
- B. Safeguard critical business data by serving as a centralized system for backup and disaster
- C. Harmonize data from multiple sources with a standardized and extendable data model.
- D. Understand and act upon customer data to drive more relevant experiences.
Answer: C,D
Explanation:
recovery.
Explanation:
Data Cloud is a data platform that can help customers connect, prepare, harmonize, unify, query, analyze, and act on their data across various Salesforce and external sources. Some of the common use cases that can be addressed with Data Cloud are:
Understand and act upon customer data to drive more relevant experiences. Data Cloud can help customers gain a 360-degree view of their customers by unifying data from different sources and resolving identities across channels. Data Cloud can also help customers segment their audiences, create personalized experiences, and activate data in any channel using insights and AI.
Harmonize data from multiple sources with a standardized and extendable data model. Data Cloud can help customers transform and cleanse their data before using it, and map it to a common data model that can be extended and customized. Data Cloud can also help customers create calculated insights and related attributes to enrich their data and optimize identity resolution.
The other two options are not common use cases for Data Cloud. Data Cloud does not provide data governance or backup and disaster recovery features, as these are typically handled by other Salesforce or external solutions.
Reference:
Learn How Data Cloud Works
About Salesforce Data Cloud
Discover Use Cases for the Platform
Understand Common Data Analysis Use Cases
NEW QUESTION # 127
A consultant is preparing to implement Data Cloud.
Which ethic should the consultant adhere to regarding customer data?
- A. Collect and use all of the data to create more personalized experiences.
- B. Map sensitive data to the same DMO for ease of deletion.
- C. Carefully consider asking for sensitive data such as age, gender, or ethnicity.
- D. Allow senior leaders in the firm to access customer data for audit purposes.
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 # 128
A company wants to test its marketing campaigns with different target populations.
What should the consultant adjust in the Segment Canvas interface to get different populations?
- A. Segmentation filters, direct attributions, and data sources
- B. Direct attributes, related attributes, and population filters
- C. Population filters and direct attributes
- D. Direct attributes and related attributes
Answer: B
Explanation:
Segmentation in Salesforce Data Cloud:
* The Segment Canvas interface is used to define and adjust target populations for marketing campaigns.
NEW QUESTION # 129
Which information is provided in a .csv file when activating to Amazon S3?
- A. The activated data payload
- B. The manifest of origin sources within Data Cloud
- C. An audit log showing the user who activated the segment and when it was activated
- D. The metadata regarding the segment definition
Answer: A
Explanation:
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]
NEW QUESTION # 130
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