The Adobe Experience Platform (AEP) Data Governance framework is fundamentally constructed upon two core components that a Data Steward configures directly within the platform. The first is Labels, which are used to classify data by applying metadata to schemas and datasets, indicating sensitivity or contractual restrictions (e.g., C1 - No Direct Marketing). The second is Policies, which are rules that define which marketing actions are permitted or restricted based on the labels applied to the data. These two elements—classifying data with labels and defining rules with policies—are the essential building blocks for setting up and enforcing data governance within AEP.

B. Communication: This is a crucial organizational activity for a successful governance strategy but is not a configurable technical component within the AEP Data Governance framework itself.

D. Permissions: Permissions refer to AEP's Access Control system, which manages user roles and what features they can access. This is distinct from the Data Governance framework, which controls how data is used in marketing actions.

1. Adobe Experience Platform

Data Governance Overview: "Adobe Experience Platform Data Governance allows you to manage customer data and ensure compliance with regulations

restrictions

and policies applicable to data use. It plays a key role within Experience Platform at various levels

including data usage labeling

data usage policies

and policy enforcement for data usage." (Source: Adobe Experience Platform Documentation

Data Governance

Data Governance overview).

2. Adobe Experience Platform

Data Usage Labels Overview: "Data usage labels allow you to classify data that reflects privacy-related considerations and contractual conditions. Labels can be applied at the schema and field level

allowing for granular classification of data." (Source: Adobe Experience Platform Documentation

Data Governance

Data usage labels overview).

3. Adobe Experience Platform

Data Usage Policies Overview: "Data usage policies are rules that describe the kinds of marketing actions that you are allowed to

or restricted from

performing on data in Experience Platform. A core use case for data usage policies is to create policies that prevent data that is labeled with certain usage restrictions from being activated to specific destinations." (Source: Adobe Experience Platform Documentation

Data Governance

Data usage policies overview).

4. Adobe Experience Platform

Access Control Overview: "Access control in Adobe Experience Platform allows you to use roles and policies to manage access permissions for Platform features... While both are called policies

access control policies are concerned with user access to Platform capabilities

whereas data usage policies are concerned with the management of marketing actions for data." (Source: Adobe Experience Platform Documentation

Access Control

Access control overview).

For a schema's data to be ingested and used within the Real-Time Customer Profile, the schema must first be enabled for Profile. A mandatory requirement of this enablement process is to designate one of the identity fields within the schema as the primary identity. This primary identity serves as the main key that Adobe Experience Platform uses to stitch together different data fragments from various sources into a single, unified customer profile. Without a designated primary identity, the system cannot uniquely identify and merge records for an individual, making the data unusable for profile creation.

B. Secondary identity: While useful for profile stitching, designating a secondary identity is optional and not a mandatory requirement for enabling a schema for Profile.

C. Identity class: This is not a configurable setting on a schema. An identity field is defined by an identity namespace (e.g., Email, ECID), not an "identity class."

1. Adobe Experience Platform Documentation

Schemas User Guide

"Enable the schema for use in Real-Time Customer Profile." This official guide explicitly states: "To enable a schema for use in Profile

it must have a primary identity specified. The primary identity is a unique identifier that allows data from different sources to be stitched together to form a single profile view."

Source: Adobe Experience League

Schemas User Guide. Navigate to the section on creating and editing schemas in the UI.

2. Adobe Experience Platform Documentation

Real-Time Customer Profile Guide

"Profile overview." This document details the fundamentals of profile creation

explaining: "When data is ingested into Experience Platform

Real-Time Customer Profile checks to see if a profile fragment already exists for the primary identity provided in the record. If no fragment exists

it creates a new one." This highlights the foundational role of the primary identity.

Source: Adobe Experience League

Real-Time Customer Profile Guide.

3. Adobe Experience Platform Documentation

Identity Service Guide

"Identities." This resource clarifies the roles of different identities: "Each schema that is enabled for Profile must have one field designated as a primary identity. Real-Time Customer Profile uses this identity to stitch together data from different sources to create a single

unified profile for each individual."

Source: Adobe Experience League

Identity Service Guide.

The Profiles overview dashboard in Adobe Real-time Customer Data Platform provides a high-level summary of your organization's profile data. Among the standard, out-of-the-box widgets are "Profiles added" and "Profiles by source". The "Profiles added" widget displays a line graph showing the number of new profiles ingested daily over the last 30 days. The "Profiles by source" widget shows a bar chart of the top five sources contributing to the total profile count, helping users understand where their customer data originates. These widgets are fundamental for monitoring profile growth and data ingestion patterns.

C. Identity graph: This is a separate visualization tool within the "Identities" section of the UI used to explore relationships between identities, not a standard widget on the Profiles overview dashboard.

D. Identity overlap: This is a specific report, also found under the "Identities" section, that visualizes the overlap between different identity namespaces, not a default overview dashboard widget.

1. Adobe Experience Platform Documentation

Real-time Customer Profile UI guide: This official guide details the components of the Profile UI. The "Profile overview" section explicitly lists and describes the standard widgets.

Section: "Profile overview"

Details: The documentation states

"The Profiles added widget displays a line graph showing the number of profiles added to the Profile store each day for the last 30 days." It also describes the "Profiles by source widget [which] displays the top five sources from which your profiles are being composed." This directly confirms options A and B.

Source: Adobe Experience League

"Real-time Customer Profile UI guide"

Accessed October 2023.

2. Adobe Experience Platform Documentation

Identity Service UI guide: This document describes features related to identities

confirming that "Identity graph" and "Identity overlap" are distinct features located elsewhere in the UI.

Section: "Identity overlap report" and "Identity graph viewer"

Details: The guide explains that the "Identity overlap report" and the "Identity graph viewer" are tools available under the "Identities" tab in the Platform UI

separate from the main "Profiles" overview dashboard. This confirms options C and D are incorrect in the context of the question.

Source: Adobe Experience League

"Identity Service UI guide"

Accessed October 2023.

For privacy-safe audience matching, advertising and social destinations require Personally Identifiable Information (PII) like email addresses to be hashed. Adobe Experience Platform documentation specifies that the Facebook Custom Audiences, Google Customer Match, and LinkedIn Matched Audiences connectors all mandate the transformation of email addresses into the SHA256 format. Experience Platform can perform this hashing automatically during the activation workflow. These platforms use the hashed value to match users in their systems without processing clear-text PII. Other destination types, like cloud storage or certain marketing automation platforms, do not have this mandatory hashing requirement for their primary function.

B. Amazon S3 is a cloud storage destination; data formatting (like hashing) is determined by the user's export configuration, not a mandatory requirement for matching. Salesforce Marketing Cloud typically ingests clear-text emails.

C. This option incorrectly includes Salesforce Marketing Cloud. The Salesforce Marketing Cloud destination connector is designed to ingest subscriber data, typically with clear-text email addresses for direct communication, and does not mandate SHA256 hashing for identity.

1. Facebook Custom Audiences: Adobe Experience Platform Documentation

"Facebook Custom Audiences destination". In the "Supported identities" section

it explicitly lists EmailSHA256 as the target identity namespace. The "ID matching requirements" section states

"For identifiers such as email addresses or phone numbers

you must provide the data in hashed format."

2. Google Customer Match: Adobe Experience Platform Documentation

"Google Customer Match destination". The "Prerequisites" section notes

"When activating email addresses to Google Customer Match

you must use the EmailSHA256 namespace. Experience Platform handles the hashing of the email addresses automatically."

3. LinkedIn Matched Audiences: Adobe Experience Platform Documentation

"LinkedIn Matched Audiences destination". In the "Map identity" step description

it instructs

"When mapping email addresses to LinkedIn

make sure to hash them using the SHA256 algorithm... To do this

select the Apply transformation checkbox."

4. Salesforce Marketing Cloud (Incorrect Inclusion): Adobe Experience Platform Documentation

"Salesforce Marketing Cloud destination". The "Supported identities" section lists contactKey and Email as target identities

not EmailSHA256. The documentation does not mention a mandatory hashing requirement for email addresses.

Edge segmentation is the correct choice for same-page and next-page personalization because it evaluates segments with extremely low latency directly on the Adobe Experience Platform Edge Network. As data is collected from a user's interaction, segment qualification happens instantaneously, allowing for immediate personalization on the current page or the very next one the user visits. This process avoids the latency inherent in sending data to the central Real-Time CDP store for processing, which is crucial for in-the-moment user experiences.

A. Streaming segmentation: While it offers near real-time qualification, it processes data as it arrives at the central platform, which introduces more latency than edge evaluation, making it less ideal for instantaneous, same-page personalization.

C. Batch segmentation: This method processes data on a fixed schedule (typically daily), making it unsuitable for any real-time use case as segment qualifications are not updated immediately after a user's action.

1. Adobe Experience League Documentation - Segmentation overview: This document explicitly contrasts the evaluation methods. It states

"Edge segmentation: The ability to evaluate segments in Experience Platform instantaneously on the Edge Network

allowing for same-page and next-page personalization use cases."

Source: Adobe Experience Platform Documentation

"Segmentation overview

" Section: "Evaluation methods."

2. Adobe Experience League Documentation - Edge segmentation: This guide details the specific purpose of edge segmentation. It clarifies

"The primary benefit of performing segmentation on the Edge is that it allows for same-page and next-page personalization use cases... evaluation is performed as data is streamed into Platform

rather than running a segmentation job on existing data in the data lake."

Source: Adobe Experience Platform Documentation

"Edge segmentation

" Section: "Introduction to edge segmentation."

3. Adobe Experience League Documentation - Batch and streaming segmentation: This page describes the other methods

highlighting their different latency characteristics. For batch

it notes

"A new segmentation job is created every 24 hours." For streaming

it notes qualification happens as data flows in

but the context is always data arriving at the central service

not at the edge.

Source: Adobe Experience Platform Documentation

"Create a segment

" Section: "Batch and streaming segmentation."

Adobe Experience Platform (AEP), the foundation of Real-Time CDP, provides an event-based alerting system. To receive notifications for data ingestion errors from a source connection, a user must subscribe to alerts for the specific dataflow. The system offers predefined alert types, including Source flow run failed. By subscribing to this alert for a particular source dataflow, the practitioner will receive a notification—either in the UI or via email—whenever that specific data ingestion process encounters a critical error and fails to complete successfully. This is the direct and intended method for this use case.

B. Subscribe to failure alerts from monitoring Ul: This is imprecise. While you can access dataflow monitoring from the UI, the subscription action is tied specifically to a dataflow's properties, not a generic subscription "from the monitoring UI."

C. Create failure alerts in source workflow: This is incorrect terminology. Users do not "create" alerts within the source dataflow (referred to as a workflow here). Instead, they "subscribe" to existing, system-defined alert types.

1. Adobe Experience Platform Documentation

Sources > UI guides > Subscribe to sources alerts in the UI.

Section: "Subscribe to alerts"

Content: This document explicitly states

"This document provides steps on how to subscribe to email alerts for your source dataflows in the UI." It then lists the available alert types

which include Source flow run failed

directly supporting the terminology and action described in the correct answer.

2. Adobe Experience Platform Documentation

Sources > UI guides > Monitoring dataflows for sources in the UI.

Section: "Dataflow runs"

Content: This guide explains how to view the status of dataflow runs

including "Failed" statuses. It shows that the monitoring dashboard is for observing outcomes

while the alert subscription (described in the first reference) is the mechanism for proactive notification of those outcomes.

3. Adobe Experience Platform Documentation

Platform services > Alerts > Alerts overview.

Section: "Introduction"

Content: This document provides a high-level overview of the alerting framework

confirming that users can "subscribe to alerts for specific events

such as when a dataflow run has failed during data ingestion." This validates that subscribing to failure events for dataflows is the correct platform feature to use.

The "Timestamp ordered" merge method is the correct choice because it prioritizes data based on the event timestamp associated with each attribute. When a conflict occurs between attributes from different datasets, this method ensures the value from the most recent timestamp is used to form the unified profile. This directly addresses the requirement to have attributes from the "latest datasets" take precedence and is applied dynamically across all datasets contributing to the profile without manual intervention.

A. Dataset timestamp: This is not a valid, selectable merge method when creating a custom merge policy in the Adobe Experience Platform user interface. The available methods are "Timestamp ordered" and "Dataset precedence".

C. Dataset precedence: This method requires creating a pre-defined, static list of datasets. It prioritizes data based on a dataset's position in that list, not on the recency of the data, which contradicts the use case requirement.

1. Adobe Experience Platform

Real-Time Customer Profile Guide

"Merge policies overview."

Section: Merge methods - This section explicitly lists and defines the two available merge methods: "Timestamp ordered" and "Dataset precedence." It states

"When creating a merge policy

you can specify a merge method... There are two possible merge methods: Timestamp ordered and Dataset precedence." This confirms that "Dataset timestamp" (Option A) is not a valid choice.

Section: Timestamp ordered - The documentation describes this method: "When merging profile fragments

if a conflict occurs

the fragment with the more recent timestamp is prioritized." This directly supports the selection of Option B as it fulfills the requirement to use the latest data.

Section: Dataset precedence - This section explains: "When merging profile fragments

if a conflict occurs

the fragment from the dataset that is higher on the precedence list is prioritized." This confirms why Option C is incorrect for a use case based on data recency.

To enforce data governance for segment activation in Adobe Real-Time CDP, a practitioner must use the core components of the Adobe Experience Platform Data Governance framework. This involves creating Data Usage Policies (C), which are rules that define which data can be used for specific purposes. These policies work by evaluating the Data Usage Labels on the data within a segment against the Marketing Action (D) configured for the destination. The marketing action (e.g., "Email Targeting," "Cross-site Targeting") specifies the intended purpose of the data activation, allowing the policy engine to automatically block activations that would violate the established governance rules.

A. Destination labels: This is not a standard term within the AEP Data Governance framework. Data Usage Labels are applied to data fields in schemas, not directly to destinations. The property that categorizes a destination's purpose is the "Marketing Action".

B. Data enforcement rules: This is a generic description, not the specific name of the feature. "Data Usage Policies" is the precise term for the rules created and enforced within Adobe Experience Platform.

1. Adobe Experience Platform Documentation

"Data usage policies overview." This document states

"Data usage policies are rules that describe the kinds of marketing actions that you are allowed to

or restricted from

performing on data in Experience Platform. A policy definition is composed of a series of conditions based on marketing actions and the data usage labels that are applied to your data." This directly links Data Usage Policies (C) and Marketing Actions (D) as the core components for enforcement.

2. Adobe Experience Platform Documentation

"Data Governance overview." In the "Key terminology" section

it defines a Policy as "A rule that defines or restricts the marketing actions that can be performed on data that has certain labels." It also defines Marketing action as "An action that an Experience Platform data consumer can take

for which a data usage policy can be checked to determine if a policy violation has occurred." This confirms that both are essential and distinct components used by the practitioner.

3. Adobe Experience Platform Documentation

"Data usage policies user guide." The guide for creating a policy explicitly lists "Select a marketing action" as a required step in the process. This demonstrates that a practitioner must directly use and configure the Marketing Action (D) to create an effective Data Usage Policy (C).

The primary value demonstrated in the scenario is the shift from a slow, 7-day batch process to a near real-time data stream for audience activation. This change directly impacts two key areas: speed and campaign effectiveness.

1. Time-to-market (B) is a direct measure of the operational improvement. The time required to activate a segment of "likely-to-churn" customers in Facebook has been reduced from up to 7 days to near real-time. This acceleration is a core value proposition of Real-Time CDP.

2. Cost Per Action/Acquisition (CPA) (C) measures the campaign's financial efficiency and effectiveness. By targeting customers with more timely and relevant data, the retention campaign is more likely to succeed, leading to a higher conversion rate (i.e., more customers retained). This improved performance results in a lower cost for each successful retention action, directly reflecting the value of the new system.

A. CPM: Cost Per Mille (CPM) measures the cost of ad impressions, not the effectiveness of the campaign in driving a specific business outcome like customer retention.

D. AOV: Average Order Value (AOV) is irrelevant in this context, as the campaign's goal is to prevent customer churn, not to increase the value of a sales transaction.

1. Adobe Experience League

Real-Time Customer Data Platform Documentation. The overview emphasizes activating profiles "throughout the customer journey." The value in this scenario comes from acting on a churn signal at the right moment

which was previously delayed. This speed is captured by "Time-to-market." (Source: Adobe Experience League

"Real-Time Customer Data Platform Overview

" Section: "What is Real-Time Customer Data Platform?").

2. Adobe Business Whitepaper

"Reimagine the Customer Journey with a New Breed of CDP." This document discusses how a Real-Time CDP enables businesses to "deliver the next best experience in the moment" and "improve marketing ROI." A lower CPA is a primary indicator of improved marketing ROI and campaign performance

which is achieved by acting on timely data. (Source: Adobe

"Reimagine the Customer Journey with a New Breed of CDP

" Page 4

Section: "Improve marketing ROI").

3. Adobe Experience League

"Sources and Destinations." The documentation on streaming destinations like the Facebook Conversions API connector highlights the ability to "send audience and event data... in near real-time." This capability directly enables a reduction in "Time-to-market" for audience activation compared to batch file uploads. (Source: Adobe Experience League

"Destinations Overview

" Section: "Streaming destinations").

A data governance policy violation in Adobe Real-Time CDP occurs when an action, such as activating a segment, conflicts with a policy associated with the data. The C4 label indicates a contractual restriction, which is being violated by sending it to an email destination. To resolve this while upholding the existing policy, the practitioner must alter the action.

The recommended resolutions are:

1. Modify the segment (B): The practitioner can edit the segment definition to remove the specific attribute that carries the C4 label. This makes the segment compliant with the policy, allowing it to be activated.

2. Cancel the activation (C): The practitioner can stop the activation of this segment to the specific destination, thereby ceasing the action that causes the violation.

A. Remove or modify data usage policy: This is incorrect because the question explicitly requires the practitioner to "maintain existing data governance policy," not change it.

D. Remove or modify labels of the dataset: This is incorrect because modifying a data label is only appropriate if the label was applied in error. Changing a correct label to bypass a policy circumvents the governance framework rather than maintaining it.

1. Adobe Experience League - Data Governance Overview: The documentation states

"Data Governance enforces data usage policies to prevent data that is in violation of a policy from being sent to a destination." This confirms that the system's response is to block the activation

making the logical user resolutions either to stop the activation (C) or change what is being activated to make it compliant (B). (See Section: "Data activation")

2. Adobe Experience League - Monitor data governance policy compliance: This document describes the workflow when a violation occurs: "If a policy is violated

the activation workflow is prevented from continuing... Once you have addressed the issue (for example

by removing the... data from the segment)

you can try activating the segment again." This directly supports modifying the segment (B) as a primary resolution. (See Section: "Policy enforcement")