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| Section | Objectives |
|---|---|
| Identity Resolution | - Explain the purpose and configuration of Identity Resolution - Describe matching and reconciliation rules |
| Data Ingestion and Modeling | - Explain data modeling concepts including Data Model Objects (DMOs) - Describe data streams and data sources |
| Data Cloud Overview | - Explain the purpose and functionality of Data Cloud - Describe the Data Cloud ecosystem and how it fits into the Salesforce platform |
| Data Cloud Reporting and Analytics | - Utilize Data Cloud reports and dashboards |
| Data Cloud Setup and Administration | - Configure Data Cloud settings - Manage Data Cloud permissions and security |
| Activation | - Configure activations to various targets - Describe activation use cases |
| Segmentation and Calculated Insights | - Create and manage segments - Explain calculated insights |
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NEW QUESTION # 32
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
Answer: A
Explanation:
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. References:
Manage Access with Data Cloud Permission Sets
Object Permissions
NEW QUESTION # 33
Every day, Northern Trail Outfitters (NTO) uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3 bucket, and files older than 7 days are automatically deleted. Each file contains a timestamp in a standardized naming convention. What should a consultant consider when ingesting this data stream?
Answer: A
Explanation:
Explanation
This configuration will ensure that Data Cloud only ingests new files from the Amazon S3 bucket and updates or inserts new records into the data stream without deleting existing records.
References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_amazon_s3.htm&type=5
NEW QUESTION # 34
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company.
Which action is essential to effectively begin the Data Cloud lifecycle?
Answer: A
Explanation:
Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
Identifying Use Cases:
Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
Actions:
Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
Step 2: Identify and catalog the required data sources for these use cases.
Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
References:
Salesforce Data Cloud Implementation Guide
Salesforce Data Cloud Lifecycle
NEW QUESTION # 35
What are the two distinct phases of data model management in Data Cloud?
Answer: B,D
Explanation:
These two phases are distinct phases of data model management in Data Cloud. Data ingestion is the process of bringing data from different sources into Data Cloud using connectors or APIs. Data modeling is the process of mapping the ingested data to the Data Cloud canonical model or creating custom data model objects. Reference: https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_model.htm&type=5
NEW QUESTION # 36
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
Answer: C
Explanation:
The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. References:
Use Value Suggestions in Segmentation
NEW QUESTION # 37
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