Pass the Salesforce Salesforce Data Cloud Data-Cloud-Consultant Questions and answers with CertsForce

The correct answer is B, Unified Individual. A Unified Individual is a record that represents a customer across different data sources, created by applying identity resolution rulesets. Identity resolution rulesets are sets of match and reconciliation rules that define how to link and merge data from different sources based on common attributes. Data Cloud uses identity resolution rulesets to resolve data across multiple data sources and helps you create one record for each customer, regardless of where the data came from1. A retail customer who wants to bring customer data from different sources and use identity resolution for segmentation should segment on the Unified Individual entity, which contains the resolved and consolidated customer data. The other options are incorrect because they do not represent the resolved customer data across different sources. A Subscriber is a record that represents a customer who has opted in to receive marketing communications. A Unified Contact is a record that represents a customer who has a relationship with a specific business unit. An Individual is a record that represents a customer’s profile data from a single data source. References:

Identity Resolution Ruleset Processing Results

Consider Data Implications for Segmentation

Prepare for your Salesforce Data Cloud Consultant Credential

AI-based Identity Resolution: Linking Diverse Customer Data

To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:

Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.

Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity’s identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:

Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.

Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:

Delete Individuals from Data Cloud

Requesting Data Deletion or Right to Be Forgotten

Data Refresh for Data Cloud

[Data Explorer]

 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.

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.

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

To meet the requirement of targeting loyal and engaged customers (platinum-tier customers visiting investment pages more than three times in 24 hours) and sending an immediate email offering a private consultation, the best solution is to use a streaming insight with a data action into a journey in Marketing Cloud Engagement . Here’s why:

Understanding the Requirement

The company wants to identify platinum-tier customers who visit their Investment pages more than three times within a 24-hour period.

Once identified, these customers should immediately receive an email offering a private consultation.

This requires real-time monitoring of customer behavior and triggering an automated response.

Why Streaming Insight with a Data Action?

Streaming Insights for Real-Time Monitoring :

A streaming insight in Salesforce Data Cloud monitors customer interactions in real time.

It can detect when a platinum-tier customer visits the Investment pages more than three times within 24 hours.

Data Actions for Immediate Response :

A data action allows you to trigger specific actions based on the insights generated.

In this case, the data action would send the customer's information to a journey in Marketing Cloud Engagement to initiate the email campaign.

Journey in Marketing Cloud Engagement :

Marketing Cloud Engagement journeys are designed to automate personalized marketing activities, such as sending transactional emails.

By integrating the streaming insight with a journey, the system can immediately send the email offering a private consultation.

Steps to Implement This Solution

Step 1: Create a Streaming Insight

Navigate to Data Cloud > Insights > Streaming Insights .

Define the criteria for identifying platinum-tier customers who visit the Investment pages more than three times in 24 hours.

Step 2: Configure a Data Action

Set up a data action that sends the identified customer's information to Marketing Cloud Engagement.

Ensure the data action includes relevant details (e.g., customer ID, email address).

Step 3: Build a Journey in Marketing Cloud Engagement

In Marketing Cloud Engagement, create a journey that listens for incoming data from the data action.

Configure the journey to send a personalized email offering a private consultation.

Step 4: Test and Deploy

Test the entire workflow to ensure that the streaming insight triggers the data action and that the email is sent immediately.

Why Not Other Options?

A. Calculated insight with a data action to a Marketing Cloud Engagement transactional email :Calculated insights are not designed for real-time monitoring. They are better suited for batch processing or periodic calculations, making them unsuitable for this use case.

B. Rapid segment to a data action journey in Marketing Cloud Engagement :While rapid segments are useful for quickly grouping customers, they do not provide the real-time detection required for this scenario.

C. Standard segment with activation into Marketing Cloud Engagement :Standard segments are static or periodically updated and cannot respond to real-time customer behavior.

Conclusion

By using a streaming insight with a data action into a journey in Marketing Cloud Engagement , Cumulus Financial can achieve real-time monitoring and immediate engagement with its loyal customers.

To use the Amazon S3 Storage Connector in Data Cloud, the consultant needs to provide the S3 bucket name, region, and access key and secret key for authentication. The access key and secret key are generated by AWS and can be managed in the IAM console. The other options are not supported by the S3 Storage Connector or by Data Cloud. References: Amazon S3 Storage Connector - Salesforce, How to Use the Amazon S3 Storage Connector in Data Cloud | Salesforce Developers Blog

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 Data Stream Deployment: When setting up a data stream in Salesforce Data Cloud, the initial deployment requires a comprehensive data load.

 Types of Refreshes:

Incremental Refresh: Only updates with new or changed data since the last refresh.

Manual Refresh: Requires a user to manually initiate the data load.

Partial Refresh: Only a subset of the data is refreshed.

Full Refresh: Loads the entire dataset into the system.

 First-Time Deployment: For the initial deployment of a data stream, a full refresh is necessary to ensure all data from the source system is ingested into Salesforce Data Cloud.

 References:

Salesforce Documentation: Data Stream Setup

Salesforce Data Cloud Guide

NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel’s preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations