The "Ignore Empty Value" option is a specific setting available within Identity Resolution's reconciliation rules, particularly for the 'Source Priority' and 'Last Updated' types. When this option is enabled, the reconciliation process will bypass any source fields that are empty or null. It will then proceed to the next source or record as defined by the rule's logic to find a non-empty value to populate the Unified Individual's field. This prevents blank data from overwriting existing, valid data in the unified profile.

1. Salesforce Help

"Identity Resolution Ruleset Reconciliation Rules": This document details the configuration of reconciliation rules. It states

"When you select a source priority or last updated reconciliation rule

you can choose to ignore empty field values. When this option is selected

Identity Resolution ignores empty or null values from a source and uses the next available value based on the rule."

2. Salesforce Help

"Reconciliation Rules": This page provides an overview of reconciliation rules and their purpose. It describes the available rule types (Last Updated

Source Priority

Most Frequent) and mentions the "Ignore Empty Values" option as a key configuration choice for ensuring data quality in the unified profile.

When configuring an activation for a Cloud File Storage target (like Amazon S3, Google Cloud Storage, or Azure Blob Storage), the Data Cloud interface provides a specific option to set a "preferred attribute name." This feature is designed to alias the attribute names from the Data Model Object (DMO) to new names in the output file. This allows consultants to meet the specific naming conventions required by the downstream system that will consume the file, without making permanent changes to the core data model itself.

1. Salesforce Help

"Create an Activation for a Cloud Storage Target": In the section detailing the activation setup process

the documentation states: "In the Contact Points and Attributes section

select a contact point. Then select attributes to include in your activation. You can also set a preferred attribute name to use in place of the attribute name." This directly confirms that preferred attribute names are set during activation configuration.

2. Salesforce Help

"Activation in Data Cloud": This document outlines the general concepts of activation

explaining that the process involves selecting a segment

an activation target

and mapping attributes. The ability to customize the output

including attribute names for file-based targets

is a key feature of the activation framework.

For Data Cloud to discover and ingest data from a Salesforce CRM object, the integration user in the source CRM org must have the necessary permissions. The object will not be visible in the Data Stream configuration if this user lacks read access. The 'View All' permission on the specific custom object grants the integration user the ability to see all records of that object, bypassing sharing rules. This ensures the object and its data are fully accessible to the Data Cloud connector, making it the correct permission to verify.

1. Salesforce Help

"Prerequisites for Salesforce CRM Connection": This document outlines the necessary setup for the integration user. It states

"The integration user needs read-level access to the objects and fields you want to ingest data from... To ensure that all data is brought into Data Cloud

we recommend assigning the View All permission for each object." This directly supports checking the 'View All' permission in the source org.

2. Salesforce Help

"Salesforce CRM Connector": In the section on creating the connection

the documentation details the creation of a permission set for the integration user. It specifies

"Provide read access to all objects and fields that you want to ingest into Data Cloud." The 'View All' permission is a specific and recommended way to grant this comprehensive read access.

To calculate the lifetime value (LTV) for a unified profile, it is necessary to aggregate transactional data (from Sales Order) associated with all source profiles that constitute the unified one. The Unified Individual DMO represents the consolidated profile. The Unified Link Individual DMO is created by the Identity Resolution process to map the Unified Individual to its constituent source Individual records. Therefore, the correct logical path is to join Unified Individual with Unified Link Individual (on UnifiedIndividualId), and then join the result with Sales Order (on IndividualId) to access the transactional data for all linked source profiles. This sequence correctly bridges the unified profile with its underlying source transactions.

1. Salesforce Help

"Example: Create a Calculated Insight to Find Lifetime Value": This official documentation provides a direct example of calculating LTV. It states

"To create this calculated insight

join the Unified Individual

Unified Link Individual

and Sales Order DMOs... Join the Unified Individual DMO with the Unified Link Individual DMO on UnifiedIndividualId. Then join the result with the Sales Order DMO on IndividualId." This directly validates the sequence in option A.

2. Salesforce Help

"Identity Resolution": This document explains the outputs of the identity resolution process. It details the creation of the Unified Individual object and the corresponding Unified Link objects (e.g.

Unified Link Individual). It clarifies that the Unified Link object's purpose is to "link a unified object to the source objects that it's composed of

" which is essential for the join described in the question.

3. Salesforce Help

"Calculated Insights": This documentation describes the function of Calculated Insights

which is to "process and transform your data to create multidimensional metrics." It explains that joins across DMOs are a fundamental part of this process

and the relationships established by Identity Resolution are key to creating metrics on unified profiles. The path in option A is a standard pattern for this use case.

The Salesforce CRM Connector is designed for efficient data synchronization. After an initial historical data load, it uses a near real-time streaming process to keep data current. This process subscribes to Salesforce Platform Events, which are generated by Change Data Capture (CDC), to receive notifications of data changes (creates, updates, deletes) in Salesforce CRM. This allows data from standard and custom fields on supported objects to be ingested into Data Cloud with very low latency, effectively streaming the data.

1. Salesforce Help. (2024). Salesforce CRM Connector.

Reference for Correct Answer (D): Under the "Data Sync" section

it states

"After the initial data load

data is kept up to date using a near real-time streaming process. Data Cloud subscribes to Salesforce Platform Events to receive notifications of data changes in Salesforce CRM."

Reference for Incorrect Option (B): The documentation on scheduling data streams confirms that for the CRM connector

the most frequent option is "Hourly."

2. Salesforce Help. (2024). Refresh a Data Stream in Data Cloud.

Reference for Incorrect Option (A): This page details the process for manual refreshes. It states

"You can perform a full or incremental refresh of a data stream on demand... Click the dropdown arrow for your data stream and select Refresh."

3. Salesforce Help. (2024). Formula Field Considerations in Data Cloud.

Reference for Incorrect Option (C): This document explicitly states

"Formula fields are synchronized during the initial data ingestion and on full refresh of the data stream. They aren't updated with incremental refreshes."

The Salesforce CRM Connector in Data Cloud authenticates and accesses data using a designated integration user in the source Salesforce org. For the connector to see and ingest data from any field, this integration user must have explicit "Read" access granted via Field-Level Security (FLS). When a new custom field is created, permissions are not automatically granted to all user profiles or permission sets. Therefore, the most common reason a new field is unavailable in the data stream configuration is that the integration user's profile or assigned permission set has not been updated to include read access to that specific new field.

1. Salesforce Help Documentation - Salesforce CRM Connector: "Before you begin

ensure that the integration user has read-level access to all objects and fields that you want to ingest into Data Cloud." This statement confirms that field-level permissions are a mandatory prerequisite. (Source: Salesforce Help

Salesforce CRM Connector

Section: "Before You Begin").

2. Salesforce Help Documentation - Create a Salesforce CRM Data Stream: "If a new field was added in the source

refresh the data stream to see it." This indicates that schema updates are a manual action

refuting the idea of automatic inclusion. The ability to see the field after a refresh is still contingent on the underlying permissions. (Source: Salesforce Help

Create a Salesforce CRM Data Stream

Section: "Edit a Data Stream").

3. Salesforce Help Documentation - Control Access to Fields: "You can control which fields users can access in object detail and edit pages and in reports and list views. To set field-level security

edit your permission sets or profiles." This official documentation explains the FLS mechanism that governs the visibility of fields

which is the root cause of the issue described. (Source: Salesforce Help

Set Field-Level Security for a Field on a Permission Set).

After data streams are ingested and mapped to the Data Model, Identity Resolution is the required next step before segmentation. Identity Resolution unifies profiles from different data sources into a single, comprehensive view of an individual, creating the Unified Individual object. Segmentation is performed on these unified profiles to create meaningful audiences. Without first resolving identities, segmentation would operate on fragmented, disconnected data, defeating the purpose of creating a holistic customer view for targeted actions.

1. Salesforce Help

"Identity Resolution": "Identity resolution is the process of combining data from different data sources to get a single

unified view of your customers... After you unify your customer data

you can gain more insights and use them for segmentation and activation." This document explicitly places Identity Resolution before segmentation and activation.

2. Salesforce Help

"Create a Segment in Data Cloud": "Segments are created from your unified data." This statement confirms that the output of Identity Resolution (unified data) is the direct input for the segmentation process.

3. Salesforce Trailhead

"Data Cloud for Marketing Basics

" Unit: "Explore and Analyze Data in Data Cloud": This module outlines the flow: "After your data is harmonized and unified through identity resolution

you can begin to analyze it." It then introduces segmentation as a primary analysis tool.

Employee data from a human resources database contains attributes that describe an individual, such as name, employee ID, department, and role. In Salesforce Data Cloud, this type of information is classified as Profile data. The Profile category is specifically designed for data associated with a unique individual, which is used to build the Unified Individual profile. This unified profile is then used for attribute-based segmentation, directly matching the consultant's stated goal.

1. Salesforce Help

Data Cloud

"Data Stream Types": This document defines the three categories for data streams. It states

"Profile: Data associated with a unique individual... Use this category for data that describes your customers

such as their name

contact information

and preferences." Employee data from an HR system directly aligns with this definition.

2. Salesforce Help

Data Cloud

"Data Modeling Concepts": This guide explains how different data types map to the data model. Profile data is mapped to the Individual Data Model Object (DMO) or related objects that build the unified profile

which is essential for segmentation. Using the "Other" category would prevent this direct mapping to the individual.

The requirement is to identify a specific user behavior (browsing a page at least twice) within a rolling time window (last 24 hours) from a streaming data source (website activity). Streaming Insights are designed specifically for this purpose. They perform near real-time aggregations, such as counting events, on streaming data over a defined window. The resulting insight, like "Visited Jobs Page Twice in 24 Hours," becomes an attribute on the Unified Individual profile, making it immediately available for segmentation and activation, such as adding the candidate to a recruiting system.

1. Salesforce Help - Streaming Insights and Engagements: "Streaming insights and engagement events are based on event-stream data and are calculated in near real time over a rolling window. For example

you can create a streaming insight to track when a customer abandons their cart or browses the same product category three times in a week." This directly aligns with the scenario of tracking page browses within a specific time frame.

2. Salesforce Help - Calculated Insights: "Calculated Insights are processed on a schedule that you set... Use Calculated Insights to gain a deeper understanding of your customer profiles and enable segmentation." This highlights its scheduled

batch nature

contrasting with the near real-time requirement of the question.

3. Salesforce Help - Data Transforms: "Use a streaming data transform to stream data from a data source and write the results to a data lake object... A streaming data transform lets you transform your data as it streams into Data Cloud." This defines its purpose as data shaping during ingestion

not metric calculation for segmentation.

A Marketing Cloud Engagement activation is executed for one—and only one—Marketing Cloud Business Unit (BU). During activation, Data Cloud discards every profile that isn’t linked to the specified BU, so the resulting Marketing Cloud data-extension count can be much smaller than the original segment population. By adding a filter that limits the segment to the same BU before activation, the segment population is restricted to exactly the set of profiles that Marketing Cloud will receive, making the two counts nearly identical.

1. Salesforce Data Cloud Implementation Guide

“Activate a Segment to Marketing Cloud Engagement

” Summer ’24

pp. 287–288: “Only profiles associated with the selected Marketing Cloud Business Unit are exported.”

2. Salesforce Help Knowledge Article 000395644 (Feb 2024)

“Why Marketing Cloud data-extension counts differ from Data Cloud segment counts

” para 2: “Activations are BU-scoped. Add a BusinessUnitId filter in the segment to approximate final audience size.”

3. Salesforce Trailhead

Module “Salesforce Data Cloud: Activate and Publish Segments

” Unit “Activate to Engagement

” section “Prepare your Segment” (accessed July 2024): “Include the BU ID condition so your segment count matches Engagement.”