Azure Data Factory preguntas y respuestas de entrevista
Pregunta 16. How can you parameterize datasets in Azure Data Factory?
Datasets can be parameterized using expressions and system variables to make them more dynamic and adaptable to changing requirements.
Pregunta 17. What is the purpose of Azure Data Factory managed private endpoints?
Managed private endpoints allow you to securely access data stores over a private connection, extending the data factory's network into the data store's virtual network.
Pregunta 18. Explain the concept of data slicing in Azure Data Factory.
Data slicing is the division of data into time-based slices, which is often used in incremental data loading scenarios in data pipelines.
Pregunta 19. How does Azure Data Factory support hybrid data scenarios?
Azure Data Factory supports hybrid data scenarios through on-premises data gateways, which allow data movement between on-premises and cloud data stores.
Pregunta 20. What is the purpose of data partitioning in Azure Data Factory?
Data partitioning is used to divide large datasets into smaller, more manageable partitions to improve processing efficiency and parallelism.
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