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| Section | Objectives |
|---|---|
| Topic 1: Data Cloud Setup and Administration | - Configure Data Cloud settings - Manage Data Cloud permissions and security |
| Topic 2: Activation | - Describe activation use cases - Configure activations to various targets |
| Topic 3: Data Cloud Reporting and Analytics | - Utilize Data Cloud reports and dashboards |
| Topic 4: Identity Resolution | - Explain the purpose and configuration of Identity Resolution - Describe matching and reconciliation rules |
| Topic 5: Data Cloud Overview | - Describe the Data Cloud ecosystem and how it fits into the Salesforce platform - Explain the purpose and functionality of Data Cloud |
| Topic 6: Segmentation and Calculated Insights | - Explain calculated insights - Create and manage segments |
| Topic 7: Data Ingestion and Modeling | - Explain data modeling concepts including Data Model Objects (DMOs) - Describe data streams and data sources |
>> 最新Salesforce-Data-Cloud題庫資訊 <<
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問題 #91
Which two applications automatically create activation targets at the time the application is connected to Data Cloud?
答案：C,D
解題說明：
These two applications automatically create activation targets when they are connected to Data Cloud.You can use these targets to activate segments or calculated insights to these applications.References:https://help.
salesforce.com/s/articleView?id=sf.c360_a_data_cloud_activation.htm&type=5
問題 #92
Which feature can integrate in real time with Salesforce CRM?
答案：D
解題說明：
This feature can integrate in real time with Salesforce CRM. Data Actions allow you to perform actions on Salesforce CRM records based on Data Cloud data, such as creating, updating, or deleting records. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_actions.htm&type=5
問題 #93
What is a typical use case for Salesforce Data Cloud?
答案：A
解題說明：
A typical use case for Salesforce Data Cloud is data harmonization across multiple platforms . Here's why:
Understanding Salesforce Data Cloud
Salesforce Data Cloud is designed to aggregate, unify, and analyze customer data from multiple sources, including CRM, Marketing Cloud, external systems, and third-party platforms.
Its primary purpose is to provide a unified view of customer data for personalized experiences and actionable insights.
Why Data Harmonization Across Multiple Platforms?
Data Harmonization :
Data Cloud harmonizes data by standardizing and cleansing it from disparate sources.
This ensures consistency and accuracy across platforms, enabling organizations to create a single source of truth for customer data.
Use Case Alignment :
Data harmonization is a core functionality of Data Cloud, making it the most relevant use case among the options provided.
Other Options Are Less Relevant :
A). Data synchronization across the Salesforce ecosystem : While Data Cloud integrates with Salesforce products, its primary focus is on unifying data from multiple platforms, not just Salesforce.
B). Storing CRM data on premises : Data Cloud is a cloud-based solution and does not support on-premises storage.
D). Sending personalized emails at scale : This is a use case for Marketing Cloud, not Data Cloud.
Steps to Achieve Data Harmonization
Step 1: Ingest Data
Bring in customer data from multiple sources (e.g., CRM, Marketing Cloud, external systems) into Data Cloud.
Step 2: Standardize and Cleanse Data
Use batch or streaming transformations to standardize formats, remove duplicates, and cleanse data.
Step 3: Create Unified Profiles
Use identity resolution to merge related records into a single unified profile.
Step 4: Activate Insights
Leverage the harmonized data for segmentation, personalization, and analytics.
Conclusion
The most typical use case for Salesforce Data Cloud is data harmonization across multiple platforms , enabling organizations to unify and leverage customer data effectively.
問題 #94
A consultant needs to publish segment data to the Audience DMO that can be retrieved using the Query APIs.
When creating the activation target, which type of target should the consultant select?
答案：D
問題 #95
What is a DMO called if it inherits the name, shape, and semantics of the reference object?
答案：B
解題說明：
A Data Model Object (DMO) that inherits the name, shape, and semantics of the reference object is called a Standard DMO. A reference object is a predefined object in the Data Cloud data model that represents a common entity or concept, such as Individual, Order, or Product. A Standard DMO is a copy of a reference object that you can use to ingest data from a specific source without modifying the original reference object. A Standard DMO has the same fields and relationships as the reference object, but you can add custom fields or relationships to it if needed. Reference: Data Model Objects
問題 #96
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