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Salesforce Data-Cloud-Consultant Exam Sample Questions

Question # 1

How does Data Cloud ensure high availability and fault tolerance for customer data?

A. By distributing data across multiple regions and data centers

B. By using a data center with robust backups

C. By Implementing automatic data recovery procedures

D. By limiting data access to essential personnel

Answer

A. By distributing data across multiple regions and data centers

Explanation: Ensuring High Availability and Fault Tolerance: High availability refers to systems that are continuously operational and accessible, while fault tolerance is the ability to continue functioning in the event of a failure. Reference: Salesforce High Availability and Fault Tolerance Whitepaper Data Distribution Across Multiple Regions and Data Centers: Salesforce Data Cloud ensures high availability by replicating data across multiple geographic regions and data centers. This distribution mitigates risks associated with localized failures. If one data center goes down, data and services can continue to be served from another location, ensuring uninterrupted service. Reference: Salesforce Infrastructure Overview Benefits of Regional Data Distribution: Redundancy: Having multiple copies of data across regions provides redundancy, which is critical for disaster recovery. Load Balancing: Traffic can be distributed across data centers to optimize performance and reduce latency. Regulatory Compliance: Storing data in different regions helps meet local data residency requirements. Reference: Salesforce Data Center Locations and Regional Data Hosting Implementation in Salesforce Data Cloud: Salesforce utilizes a robust architecture involving data replication and failover mechanisms to maintain data integrity and availability. This architecture ensures that even in the event of a regional outage, customer data remains secure and accessible. Reference: Salesforce Trust and Compliance Documentation

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Question # 2

A consultant is connecting sales order data to Data Cloud and considers whether to use the Profile, Engagement, or Other categories to map the DLO. The consultant chooses to map the DLO called Order-Headers to the Sales Order DMO using the Engagement category. What is the impact of this action on future mappings?

A. A DLO with category Engagement can be mapped to any DMO using either Profile. Engagement, or Other categories.

B. When mapping a Profile DLO to the Sales Order DMO, the category gets updated to Profile.

C. Sales Order DMO gets assigned to both the Profile and Engagement categories when mapping a Profile DLO.

D. Only Engagement category DLOs can be mapped to the Sales Order DMO. Sales Order gets assigned to the Engagement Category.

Answer

D. Only Engagement category DLOs can be mapped to the Sales Order DMO. Sales Order gets assigned to the Engagement Category.

Explanation: Data Lake Objects (DLOs) and Data Model Objects (DMOs): In Salesforce Data Cloud, DLOs are mapped to DMOs to organize and structure data. Categories like Profile, Engagement, and Other define how these mappings are used. 

Engagement Category: Mapping a DLO to the Engagement category indicates that the data is related to customer interactions and activities. 

Impact on Future Mappings: 

Engagement Category Restriction: When a DLO like Order-Headers is mapped to the Sales Order DMO under the Engagement category, future mappings of the Sales Order DMO are restricted to Engagement category DLOs. 

Category Assignment: The Sales Order DMO is assigned to the Engagement category, meaning only DLOs categorized as Engagement can be mapped to it in the future. 

Benefits: 

Consistency: Ensures consistent data categorization and usage, aligning data with its intended purpose. 

Accuracy: Helps in maintaining the integrity of data mapping and ensures that engagement-related data is accurately captured and utilized. 

References: Salesforce Data Cloud Mapping Salesforce Data Cloud Categories

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Question # 3

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

A. A standard schema containing event, profile, and transaction data is created at the time the connector is configured.

B. The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.

C. Any data streams associated with the connector will be automatically deleted upon deleting the app from Data Cloud Setup.

D. The connector schema can be updated to delete an existing field.

Answer

B. The Tenant Specific Endpoint is auto-generated in Data Cloud when setting the connector.

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Question # 4

A company is seeking advice from a consultant on how to address the challenge of having multiple leads and contacts in Salesforce that share the same email address. The consultant wants to provide a detailed and comprehensive explanation on how Data Cloud can be leveraged to effectively solve this issue. What should the consultant highlight to address this company's business challenge?

A. Data Bundles

B. Calculated Insights

C. Identity Resolution

D. Identity Resolution

Answer

C. Identity Resolution

Explanation: Issue Overview: When multiple leads and contacts share the same email address in Salesforce, it can lead to data duplication, inaccurate customer views, and inefficient marketing and sales efforts. 

Data Cloud Identity Resolution: Salesforce Data Cloud offers Identity Resolution as a powerful tool to address this issue. It helps in merging and unifying data from multiple sources to create a single, comprehensive customer profile. 

Process: 

Data Ingestion: Import lead and contact data into Salesforce Data Cloud. 

Identity Resolution Rules: Configure Identity Resolution rules to match and merge records based on key identifiers like email addresses. 

Unification: The tool consolidates records that share the same email address, eliminating duplicates and ensuring a single view of each customer. 

Continuous Updates: As new data comes in, Identity Resolution continuously updates and maintains the unified profiles. 

Benefits: 

Accurate Customer View: Reduces duplicate records and provides a complete view of each customer’s interactions and history. 

Improved Efficiency: Streamlines marketing and sales efforts by targeting a unified customer profile. 

References: Salesforce Data Cloud Identity Resolution Salesforce Help: Identity Resolution Overview

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Question # 5

Cumulus Financial uses calculated insights to compute the total banking value per branch for its high net worth customers. In the calculated insight, "banking value" is a metric, "branch" is a dimension, and "high net worth" is a filter. What can be included as an attribute in activation?

A. "high net worth" (filter)

B. "branch" (dimension) and "banking metric)

C. "banking value" (metric)

D. "branch" (dimension)

Answer

D. "branch" (dimension)

Explanation:

According to the Salesforce Data Cloud documentation, an attribute is a dimension or a measure that can be used in activation. A dimension is a categorical variable that can be used to group or filter data, such as branch, region, or product. A measure is a numerical variable that can be used to calculate metrics, such as revenue, profit, or count. A filter is a condition that can be applied to limit the data that is used in a calculated insight, such as high net worth, age range, or gender. In this question, the calculated insight uses “banking value” as a metric, which is a measure, and “branch” as a dimension. Therefore, only “branch” can be included as an attribute in activation, since it is a dimension. The other options are either measures or filters, which are not attributes.

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