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NEW QUESTION # 23
How does the Adobe Real-Time CDP manage data when multiple records, coming from different sources but belonging to the same customer, are processed?
Answer: B
Explanation:
The fundamental value proposition of Adobe Real-Time CDP is its ability to break down data silos by creating a360-degree viewof the customer. When the system ingests multiple records from different sources (such as a CRM system, an e-commerce platform, and web clickstream data) that share common identifiers, it uses theIdentity Serviceto recognize they belong to the same person.
The platform then dynamically merges these "profile fragments" into a single,unified Real-Time Customer Profile. This merging happens in real-time, ensuring that as soon as new data arrives, it is reflected in the unified view. This process allows for consistent personalization across channels; for example, a purchase made offline in a retail store can immediately suppress "buy now" ads for that same product on the website.
Option B is incorrect as it describes the very siloed state the CDP is designed to solve. Option C is incorrect because the platform preserves all relevant behavioral and attribute data rather than discarding records based on frequency. Option D is a slight misinterpretation ofMerge Policies; while Merge Policies can prioritize one source over another for a specific attribute (Timestamp-ordered or Dataset-precedence), the platform still merges the records into a single profile rather than just weighing them.
NEW QUESTION # 24
A financial services customer wishes to suppress people from active credit card campaigns as soon as they submit an application for the associated credit card name. The business's goal is to optimize ad spend by suppressing people quickly who convert and use the savings to help funnel more money back into their acquisition strategies.
The current data model that IT has provided from their data warehouse looks like the following:
It is assumed that each application submit contains an offer that is always associated to a credit card name.
Assuming all applications are streamed into the Real-Time Customer Profile, in which two ways could a developer model the application submit event to ensure the real-time suppression requirement is supported? (Choose two.)
Answer: B,C
NEW QUESTION # 25
A retail company wants to target customers who viewed a product category on their website within the last 24 hours.
What type of segmentation should they use?
Answer: D
NEW QUESTION # 26
A data engineer needs to ingest batch data from a third-party customer relationship management (CRM) system into Adobe Real-Time CDP for a major holiday marketing campaign. What should the engineer check for in the initial stages of creating a manual dataflow when considering the batch ingestion framework?
Answer: C
Explanation:
When setting up a manual batch dataflow in Adobe Experience Platform, the first technical hurdle is ensuring that the source file is compatible with the platform's ingestion engine. Adobe Real-Time CDP supports specific file formats for batch ingestion, primarilyParquetandJSON. If the CRM data is exported as a CSV, the engineer must ensure it follows strict formatting rules or convert it to a supported format to prevent ingestion failures during the validation stage.
Checking the file format (Option B) is a foundational step because the ingestion service validates the file structure against the target XDM schema immediately upon upload. While the target schema must indeed be associated with the dataset (Option A), this is a step within the dataflow creation process rather than a preliminary check of the batch data itself. Option C is a legal/governance concern rather than a technical framework requirement for dataflow creation. Option D is incorrect because batch ingestion is typically scheduled or triggered manually; it is not a "trigger-on-creation" mechanism like streaming. Ensuring the file format is correct is the primary "pre-flight" check to guarantee that the mapping interface can correctly interpret the source fields for the marketing campaign data.
NEW QUESTION # 27
A company has completed their implementation of Adobe Experience Platform (AEP) and is successfully onboarding data and profiles, but they are struggling with managing data across their services. What tool would best aid the company in inspecting, manipulating, and analyzing dataset data in AEP Data Lake?
Answer: A
Explanation:
Adobe Experience PlatformQuery Serviceis the foundational tool designed for inspecting, validating, and transforming data within theData Lake. While AEP stores data in a NoSQL environment, Query Service provides aStandard SQLinterface that allows data architects and engineers to interact with datasets as if they were relational tables. This is critical for post-ingestion data preparation and for analyzing complex customer journeys that span multiple datasets.
The service is primarily used forad hoc data exploration-allowing users to run SELECT queries to verify that ingested data matches the expected schema and quality standards before it is enabled for the Real-Time Customer Profile. Beyond simple inspection, it supportsBatch Queries(using "Create Table As Select" or CTAS) to derive new datasets from existing ones, which can then be used for reporting or re-ingested into the Profile Service.
Options A, C, and D refer to theData Governanceframework, which is used for labeling data and enforcing usage policies (DULE) or managing compliance. While these are essential for managingaccessandprivacy, they do not provide the analytical or manipulative capabilities required to query the raw data rows. Query Service remains the only tool within the platform that allows for deep SQL-based analysis of the full Data Lake history.
NEW QUESTION # 28
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