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Salesforce Data-Cloud-Consultant 考試大綱：

主題	簡介
主題 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.
主題 2	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.
主題 3	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 4	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.

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最新的 Salesforce Data Cloud Data-Cloud-Consultant 免費考試真題 (Q105-Q110):

問題 #105
Which two requirements must be met for a calculated insight to appear in the segmentation canvas?
Choose 2 answers

A. The metrics of the calculated insights must only contain numeric values.
B. The primary key of the segmented table must be a dimension in the calculated insight.
C. The calculated insight must contain a dimension including the Individual or Unified Individual Id.
D. The primary key of the segmented table must be a metric in the calculated insight.

答案：B,C

解題說明：
A calculated insight is a custom metric or measure that is derived from one or more data model objects or data lake objects in Data Cloud. A calculated insight can be used in segmentation to filter or group the data based on the calculated value. However, not all calculated insights can appear in the segmentation canvas. There are two requirements that must be met for a calculated insight to appear in the segmentation canvas:
The calculated insight must contain a dimension including the Individual or Unified Individual Id. A dimension is a field that can be used to categorize or group the data, such as name, gender, or location. The Individual or Unified Individual Id is a unique identifier for each individual profile in Data Cloud. The calculated insight must include this dimension to link the calculated value to the individual profile and to enable segmentation based on the individual profile attributes.
The primary key of the segmented table must be a dimension in the calculated insight. The primary key is a field that uniquely identifies each record in a table. The segmented table is the table that contains the data that is being segmented, such as the Customer or the Order table. The calculated insight must include the primary key of the segmented table as a dimension to ensure that the calculated value is associated with the correct record in the segmented table and to avoid duplication or inconsistency in the segmentation results.
Create a Calculated Insight, Use Insights in Data Cloud, Segmentation

問題 #106
Which statement about Data Cloud's Web and Mobile Application Connector is true?

A. The connector schema can be updated to delete an existing field.
B. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.
C. The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.
D. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.

答案：C

解題說明：
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the TSE. Reference: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream

問題 #107
Which statement about Data 360 ' s Web and Mobile Application Connector is true?

A. The connector schema can be updated to delete an existing field.
B. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data 360 Setup.
C. The Tenant Specific Endpoint is auto-generated in Data 360 when setting the connector.
D. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.

答案：C

解題說明：
The design point is to preserve source fidelity while shaping data only where Data 360 processing needs it.
Here, The Tenant Specific Endpoint is auto-generated in Data 360 when setting the connector. 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.

問題 #108
Cumulus Financial segregates its sales CRM data based on Region for its Data Cloud users. Multiple data spaces are configured: a default space and two additional spaces tailored for EMEA and APAC regions.
EME A sales reps who need temporary access to visualize data for both regions say that they cannot visualize APAC dat a. APAC sales reps can visualize the corresponding segmented data.
Which statement describes the cause of this issue?

A. The APAC data space is not associated with any permission set.
B. The EMEA sales reps have not been assigned to the profile associated with the APAC data space.
C. The APAC data space Is not associated with any profile.
D. The EMEA sales reps have not been assigned to the permission set associated with the APAC data space.

答案：D

問題 #109
Cumulus Financial uses Service Cloud as its CRM and stores mobile phone, home phone, and work phone as three separate fields for its customers on the Contact record. The company plans to use Data Cloud and ingest the Contact object via the CRM Connector.
What is the most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation?

A. Ingest the Contact object and then create a calculated insight to normalize the phone numbers, and then map to the Contact Point Phone data map object.
B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object.
C. Ingest the Contact object and create formula fields in the Contact data stream on the phone numbers, and then map to the Contact Point Phone data map object.
D. Ingest the Contact object and map the Work Phone, Mobile Phone, and Home Phone to the Contact Point Phone data map object from the Contact data stream.

答案：B

解題說明：
The most efficient approach that a consultant should take when ingesting this data to ensure all the different phone numbers are properly mapped and available for use in activation is B. Ingest the Contact object and use streaming transforms to normalize the phone numbers from the Contact data stream into a separate Phone data lake object (DLO) that contains three rows, and then map this new DLO to the Contact Point Phone data map object. This approach allows the consultant to use the streaming transforms feature of Data Cloud, which enables data manipulation and transformation at the time of ingestion, without requiring any additional processing or storage. Streaming transforms can be used to normalize the phone numbers from the Contact data stream, such as removing spaces, dashes, or parentheses, and adding country codes if needed. The normalized phone numbers can then be stored in a separate Phone DLO, which can have one row for each phone number type (work, home, mobile). The Phone DLO can then be mapped to the Contact Point Phone data map object, which is a standard object that represents a phone number associated with a contact point.
This way, the consultant can ensure that all the phone numbers are available for activation, such as sending SMS messages or making calls to the customers.
The other options are not as efficient as option B. Option A is incorrect because it does not normalize the phone numbers, which may cause issues with activation or identity resolution. Option C is incorrect because it requires creating a calculated insight, which is an additional step that consumes more resources and time than streaming transforms. Option D is incorrect because it requires creating formula fields in the Contact data stream, which may not be supported by the CRM Connector or may cause conflicts with the existing fields in the Contact object. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Streaming Transforms, Contact Point Phone

問題 #110
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