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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identity Resolution | 14% | - Conflict resolution - Unified profile creation - Matching and reconciliation rules - Identity use cases |
| Topic 2: Data Ingestion and Modeling | 20% | - Transformation and mapping - Data modeling best practices - Ingestion from various sources - Data validation and inspection |
| Topic 3: Data Cloud Setup and Administration | 12% | - Monitoring and maintenance tools - Permissions and access control - Data spaces and configuration - Data streams and data bundles |
| Topic 4: Segmentation and Insights | 18% | - Segment membership analysis - Calculated vs streaming insights - Insight implementation - Segment creation and configuration |
| Topic 5: Act on Data | 18% | - Attribute usage and management - Activation concepts and use cases - Troubleshooting activations - Process automation and triggering |
| Topic 6: Data Cloud Overview | 18% | - Core concepts and terminology - Architecture and ecosystem - Business value and use cases |
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NEW QUESTION # 89
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: B
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 # 90
During discovery, which feature should a consultant highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile?
Answer: A
Explanation:
The feature that the consultant should highlight for a customer who has multiple data sources and needs to match and reconcile data about individuals into a single unified profile is D. Identity Resolution. Identity Resolution is the process of identifying, matching, and reconciling data about individuals across different data sources and creating a unified profile that represents a single view of the customer. Identity Resolution uses various methods and rules to determine the best match and reconciliation of data, such as deterministic matching, probabilistic matching, reconciliation rules, and identity graphs. Identity Resolution enables the customer to have a complete and accurate understanding of their customers and their interactions across different channels and touchpoints. References: Salesforce Data Cloud Consultant Exam Guide, Identity Resolution
NEW QUESTION # 91
A user needs permissions to access Data Cloud to create, manage, and publish segments. However, the user should not be allowed to create reports or manage data sources. Which permission set should an administrator assign?
Answer: A
Explanation:
This permission set should be assigned to a user who needs permissions to access Data Cloud to create, manage, and publish segments, but not to create reports or manage data sources. This permission set allows the user to create and edit segments, calculated insights, streaming insights, and activations, but not to access data streams, data model, identity resolution, or reports. References:
https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_permission_sets.htm&type=5
NEW QUESTION # 92
What are the two distinct phases of data model management in Data Cloud?
Answer: C,D
Explanation:
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.
References:https://help.salesforce.com/s/articleView?id=sf.c360_a_data_cloud_data_model.htm&type=5
NEW QUESTION # 93
What is allowed when editing a Calculated Insight?
Answer: A
Explanation:
Explanation
You can add new measures or dimensions to a Calculated Insight by selecting them from the available attributes list
NEW QUESTION # 94
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