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Salesforce Data-Cloud-Consultant 考試大綱：

主題	簡介
主題 1	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.
主題 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.
主題 3	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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最新的 Salesforce Data Cloud Data-Cloud-Consultant 免費考試真題 (Q90-Q95):

問題 #90
A Data 360 Consultant is building a segment to announce a new product launch for customers who have previously purchased black pants. How should the consultant place the attributes for product color and product type from the Order Product object to meet this criteria?

A. Place the attributes for product color and product type in a single container.
B. Place the attributes for product color and product type as direct attributes.
C. Place an attribute for the " black pants " calculated insight to dynamically apply.
D. Place the attribute for product color in one container and the attribute for product type in another container.

答案：A

解題說明：
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Place the attributes for product color and product type in a single container.
works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. 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. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.

問題 #91
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?

A. Streaming insight and data action
B. Calculated insight and data action
C. Streaming insight and segment
D. Calculated insight and segment

答案：D

解題說明：
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

問題 #92
What are the two minimum requirements needed when using the Visual Insights Builder to create a calculated insight?
Choose 2 answers

A. At least one dimension
B. At least two objects to Join
C. A WHERE clause
D. At least one measure

答案：A,D

解題說明：
Introduction to Visual Insights Builder:
* The Visual Insights Builder in Salesforce Data Cloud is a tool used to create calculated insights, which are custom metrics derived from the existing data.

問題 #93
A customer has a requirement to receive a notification whenever an activation fails for a particular segment.
Which feature should the Data 360 Consultant use to solution for this use case?

A. Flow
B. Activation alert
C. Dashboard
D. Report

答案：A

解題說明：
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Flow works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. 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. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.

問題 #94
What does the Source Sequence reconciliation rule do in Identity Resolution?

A. Identifies which data sources should be used in the process of reconciliation by prioritizing the most recently updated data source
B. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name
C. Includes data from sources where the data is most frequently occurring
D. Identifies which individual records should be merged into a unified profile by setting a priority for specific data sources

答案：B

解題說明：
The identity logic is about linking source profiles safely, then choosing the best surviving values for the unified profile. Sets the priority of specific data sources when building attributes in a unified profile, such as a first or last name is appropriate because identity resolution needs reliable match inputs, qualified identifiers, and controlled reconciliation. It is not just deduplication; it is a rules-driven process that connects source records into a trusted unified profile. 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.

問題 #95
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