Azure Data Factory Interview Questions and Answers
Experienced / Expert level questions & answers
Ques 1. How does Azure Data Factory handle security?
Azure Data Factory supports Azure role-based access control (RBAC) to control access to resources. It also provides features like managed private endpoints for secure data movement.
Ques 2. Explain the concept of fault tolerance in Azure Data Factory.
Azure Data Factory provides fault tolerance through retry policies for activities, and it supports monitoring and logging for troubleshooting.
Ques 3. 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.
Ques 4. 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.
Ques 5. How can you handle schema drift in Azure Data Factory?
Schema drift is handled through mapping data flow transformations that dynamically adjust to changes in the source or destination schema during data movement.
Ques 6. 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.
Ques 7. 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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