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Adobe AD0-E605 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Destinations and Activation	16%	- Activation workflows and delivery 1. Delivery verification and troubleshooting 2. Data export and scheduling - Destination configuration and types 1. API and file-based activation 2. Built-in and custom destinations
Topic 2: Identity and Profile Management	22%	- Identity namespaces and graph 1. Identity stitching and resolution 2. Identity configuration - Profile composition and calculation 1. Merge policies 2. Profile attributes and segments
Topic 3: Privacy, Governance and Security	9%	- Security and access control 1. Role-based permissions 2. Sandbox management - Data governance framework 1. DULE labels and policies 2. Consent and compliance management
Topic 4: Architecture and Data Model	20%	- XDM schemas and data models 1. Schema design and extension 2. Data types and relationships - Platform architecture and components 1. Adobe Experience Platform foundation 2. Real-Time CDP architecture
Topic 5: Segmentation and Audience Management	15%	- Segment building and logic 1. Rule-based and calculated segments 2. Segment scheduling and evaluation - Audience creation and maintenance 1. Audience sharing and governance
Topic 6: Data Ingestion	18%	- Batch and streaming ingestion 1. Ingestion monitoring and error handling 2. Data sources configuration - Data preparation and transformation 1. Data quality management 2. Mapping and validation

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Adobe Real-Time CDP Business Practitioner Professional Sample Questions (Q17-Q22):

NEW QUESTION # 17
Which are two considerations to keep in mind when architecting data using dimensional entities?
(Choose two.)

A. Dimensional entities can be used as lookups or classifications to simplify the data modeling process.
B. Dimensional entities require secondary identities to link to profiles through schema relationships.
C. Profile data populated through dimensional entities require batch segmentation evaluation.
D. Dimensional entities can be either time series data or record data.

Answer: A,C

NEW QUESTION # 18
A marketer has a requirement to enrich the audience which was already created with a few additional attributes from a specific dataset.
Which should a marketer use to create the new enriched audience?

A. Use "Analyze audience" to add attributes to existing audience definitions
B. Create Audience with "Enrich audience" method
C. Create Audience with "Compose audience" method
D. Create Audience with "Build rule" method

Answer: C

NEW QUESTION # 19
What are characteristics of static segments? (Select two.)

A. Ideal for historical analysis and reporting.
B. Updates automatically when customer behavior changes.
C. Fixed membership that does not change over time.
D. Requires real-time data streaming.

Answer: A,C

NEW QUESTION # 20
A data engineer is tasked with creating a streaming segment, and the segment definition must include existing audiences and a page view web event. After selecting the evaluation method, an error occurs, allowing only batch evaluation to be used.
What are two possible reasons for this? (Choose two.)

A. The segment definition includes a combination of an audience and multiple page view events (last
30 days).
B. The segment definition includes a combination of an audience in multiple page view events (last
24hrs).
C. The segment definition includes a combination of an audience and a page view event (last 24hrs).
D. The segment definition includes a combination of an audience, a page view event (any time), and a profile attribute.

Answer: A,D

NEW QUESTION # 21
A media company uses Adobe Experience Platform to process large quantities of media consumption data.
This data was previously stored in a relational database management system (RDBMS) but has been migrated to the Adobe Real-Time CDP's NoSQL data model for improved scalability and performance. The data set includes information such as user ID, media content ID, play duration, pause durations, and timestamps of each interaction. Which combination of Experience Data Model (XDM) schemas should be used to efficiently capture and retrieve this data with the Adobe Real-Time CDP's NoSQL data model, considering the real-time analytics needs?

A. An XDM Individual Profile schema for user ID, media content ID and an XDM Experience Event schema for play duration, pause durations, and timestamps
B. An XDM Individual Profile schema for user ID and an XDM Experience Event schema for media consumption data
C. An XDM Experience Event schema for user ID, media content ID and an XDM Individual Profile schema for play duration, pause durations, and timestamps
D. Two XDM schemas, one for user ID and media content ID, the other for play duration, pause durations, and timestamps

Answer: B

Explanation:
In the Adobe Real-Time Customer Data Platform, the architecture is built upon theExperience Data Model (XDM), which utilizes two primary base classes to represent different types of data:XDM Individual Profile andXDM ExperienceEvent. To efficiently handle media consumption data in a NoSQL environment, it is critical to distinguish between the "actor" and the "action." TheXDM Individual Profileclass is designed to store the "record" data, representing the identity and attributes of the user (the actor). This includes theuser IDand other persistent traits like name, email, or preferences. This schema provides the centralized view of the customer. Conversely, theXDM ExperienceEventclass is purpose-built for time-series data (the actions). Media consumption data-such as content IDs, play/pause durations, and timestamps-are inherently behavioral and occur at specific points in time.
By using anExperienceEvent schemafor the media interactions, the system can capture an unlimited stream of events without bloating the profile record itself. Each event is linked to the Individual Profile via a common identity (the user ID). This separation is vital for the NoSQL data model used by theReal-Time Customer Profile, as it allows for high-throughput ingestion and enables real-time segmentation based on recent behaviors (e.g., "users who watched more than 50% of a video in the last 24 hours"). Options A, B, and C incorrectly mix behavioral event data into the profile schema or fail to leverage the standard class structure required for profile enrichment.

NEW QUESTION # 22
......

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