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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Cloud Overview and Licensing | 7% | - Describe the business value of Data Cloud - Describe Data Cloud setup and configuration - Explain licensing model and capacity |
| Topic 2: Data Actions | 8% | - Create and manage data bundles - Configure data sync to external systems - Set up segmentation and target audiences - Configure data actions for activation |
| Topic 3: Data Ingestion | 15% | - Set up and manage data connectors - Configure streaming data ingestion - Troubleshoot ingestion issues - Configure batch data ingestion - Configure data sync and refresh schedules |
| Topic 4: Data Model Setup and Configuration | 15% | - Configure custom objects, fields, and relationships - Map source data to harmonized data model - Understand data types and field mapping - Set up and configure Data Lake objects - Describe Harmonized Data Model concepts |
| Topic 5: Data Sharing and Security | 8% | - Understand data governance requirements - Configure data sharing settings - Implement row-level security - Manage user access and permissions |
| Topic 6: Data Cloud Monitoring and Troubleshooting | 22% | - Use Data Cloud analytics and reports - Debug common configuration errors - Monitor data ingestion and sync status - Manage data retention and cleanup - Troubleshoot data quality issues - Analyze identity resolution results |
| Topic 7: Identity Resolution and Data Unification | 17% | - Manage data overlap and deduplication - Configure contact and account matching - Configure match rules and strategies - Configure identity resolution rules - Understand unified records creation |
| Topic 8: Calculated Insights | 8% | - Define metrics and measurements - Publish insights to Data Cloud - Use formulas and functions in calculations - Create and configure calculated insights |
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질문 # 36
What is a reason to create a formula when ingesting a data stream?
정답：C
설명：
The design point is to preserve source fidelity while shaping data only where Data 360 processing needs it.
Here, To transform a datetime field into a date field for use in data mapping fits because it changes the shape, keying, or refresh behavior at the Data 360 layer instead of forcing the source system to carry an analytics- specific design. In production, this keeps the upstream application simpler and gives the data team a repeatable way to prepare records for mapping, identity resolution, insights, or segmentation. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data
360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably.
질문 # 37
The leadership team at Cumulus Financial has determined that customers who deposited more than $250,000 in the last five years and are not using advisory services will be the central focus for all new campaigns in the next year.
Which features support this use case?
정답：D
설명：
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.
Reference: Salesforce Data Cloud Use Case Documentation
Features Involved:
Calculated Insight: This feature helps derive metrics and values based on existing data. In this case, it can calculate total deposits over the last five years.
Segment: Segmentation allows targeting specific groups of customers based on defined criteria, such as total deposits and usage of advisory services.
Reference: Salesforce Calculated Insights and Segmentation Guide
Steps to Implement:
Create a Calculated Insight:
Navigate to Visual Insights Builder in Salesforce Data Cloud.
Create a new calculated insight to sum deposits for each customer over the last five years.
Create a Segment:
Use the Segment Canvas to create a new segment.
Apply filters to include customers with deposits over $250,000 and exclude those using advisory services.
Reference: Salesforce Calculated Insights Tutorial and Segment Creation Guide Practical Application:
Example: Identify high-value customers who are not leveraging additional services and target them with personalized marketing campaigns to promote advisory services.
Reference: Salesforce High-Value Customer Segmentation Case Study
질문 # 38
Cumulus Financial is currently using Data Cloud and ingesting transactional data from its backend system via an S3 Connector in upsert mode. During the initial setup six months ago, the company created a formula field in Data Cloud to create a custom classification. It now needs to update this formula to account for more classifications.
What should the consultant keep in mind with regard to formula field updates when using the S3 Connector?
정답：B
질문 # 39
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
정답：D
설명：
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
질문 # 40
Cumulus Financial created a segment called Multiple Investments that contains individuals who have invested in two or more mutual funds.
The company plans to send an email to this segment regarding a new mutual fund offering, and wants to personalize the email content with information about each customer's current mutual fund investments.
How should the Data Cloud consultant configure this activation?
정답：C
설명：
Explanation
To personalize the email content with information about each customer's current mutual fund investments, the Data Cloud consultant needs to add related attributes to the activation. Related attributes are additional data fields that can be sent along with the segment to the target system for personalization or analysis purposes. In this case, the consultant needs to add the Fund Name attribute, which contains the name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to "Mutual Fund" to ensure that only relevant data is sent. The other options are not correct because:
* A. Including Fund Type equal to "Mutual Fund" as a related attribute is not enough to personalize the email content. The consultant also needs to include the Fund Name attribute, which contains the specific name of the mutual fund that the customer has invested in.
* C. Adding related attribute Fund Type is not enough to personalize the email content. The consultant also needs to add the Fund Name attribute, which contains the specific name of the mutual fund that the customer has invested in, and apply a filter for Fund Type equal to "Mutual Fund" to ensure that only relevant data is sent.
* D. Including Fund Name and Fund Type by default for post processing in the target system is not a valid option. The consultant needs to add the related attributes and filters during the activation configuration in Data Cloud, not after the data is sent to the target system. References: Add Related Attributes to an Activation - Salesforce, Related Attributes in Activation - Salesforce, Prepare for Your Salesforce Data Cloud Consultant Credential
질문 # 41
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