AD0-E605 試験問題を無料オンラインアクセス

Which key distinction differentiates edge profiles from hub profiles?

• A.Edge profiles are used for batch processing, while hub profiles are for real-time actions.
• B.Edge profiles are exclusive to offline data sources, while hub profiles handle online data.
• C.Edge profiles only support structured data, while hub profiles support unstructured data.
• D.Edge profiles store data locally for low-latency processing, while hub profiles store data centrally.

A customer has noticed incorrect data was loaded into the Real-Time Customer Profile for only two profiles. The data came from a single XDM Individual Profile class-based dataset. What actions can the customer take to correct the problem?

• A.Delete the entire dataset containing the incorrect profiles
• B.Re-load all the affected profiles with the correct data and have the profile update and/or replace the existing records in the dataset
• C.Delete the batch that created the problem from the dataset in the data lake and let the profile roll- back to its previous state
• D.Look up each profile in the UI and update the incorrect attributes manually

A financial institution is using Adobe RT-CDP to activate data to an ad platform. The dataset includes sensitive information such as account balances.
What guardrails should they apply during activation?

• A.Include all data fields in the activation for completeness.
• B.Perform manual activation workflows.
• C.Limit the activation to edge-based triggers.
• D.Use DULE policies to restrict sensitive data from being exported.

What is a key feature of Edge ingestion in Adobe RT-CDP?

• A.Performing manual identity mapping during data ingestion.
• B.Processing data in central hubs for batch activation.
• C.Restricting ingestion to structured datasets only.
• D.Streaming data in real-time for immediate profile updates.

A data engineering team is tasked with onboarding data to a dataset with a substantial amount of batch data (300GB) from multiple JSON files for a historical load of customer data. What is the most efficient way for a data engineer to perform the data ingestion?

• A.Ingest the data using a database source connector
• B.Use manual upload through the UI for historical data
• C.Ingest the data using a cloud storage source connector
• D.Ingest the data using the batch ingestion API