Azure Data Factory 面试题与答案
问题 26. Explain the concept of integration patterns in Azure Data Factory.
Integration patterns in Azure Data Factory define how data is moved and transformed, providing flexibility and adaptability to different data integration scenarios.
问题 27. How does Azure Data Factory support data wrangling?
Azure Data Factory supports data wrangling through the Data Flow feature, which provides a visual interface for designing and executing data transformations.
问题 28. What is the purpose of the Azure Data Factory Mapping Data Flow?
Mapping Data Flow is a visual data transformation feature in Azure Data Factory that allows you to design and execute complex data transformations using a graphical interface.
问题 29. How can you parameterize linked services in Azure Data Factory?
Linked services can be parameterized using dynamic content expressions, allowing for dynamic configuration based on runtime values.
问题 30. Explain the concept of Azure Data Factory Managed Virtual Network.
Managed Virtual Network allows you to isolate the Azure Data Factory environment and control the network traffic for enhanced security and privacy.
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