面试题与答案

Key components include datasets, linked services, pipelines, activities, and data flows.

Data movement is achieved through activities in pipelines. Activities can be copy data activities, data flow activities, or custom activities.

A pipeline defines the overall process and workflow, while a data flow defines the data transformations within that process.

Data Flow is a cloud-based data transformation service that enables data transformations and manipulations using a visual interface.

Integration Runtimes define the compute infrastructure used by data factory for data movement and data transformation activities.

Azure Data Factory provides monitoring dashboards, logging, and integration with Azure Monitor for tracking and managing pipeline executions.

Azure Data Factory is primarily focused on data integration and ETL, while Azure Logic Apps are designed for workflow automation and business process integration.

Datasets can be parameterized using expressions and system variables to make them more dynamic and adaptable to changing requirements.

Data slicing is the division of data into time-based slices, which is often used in incremental data loading scenarios in data pipelines.

Azure Data Factory supports hybrid data scenarios through on-premises data gateways, which allow data movement between on-premises and cloud data stores.

Data Flow Debug Mode allows you to interactively debug and validate data flows during development to identify and fix issues.

Data lineage in Azure Data Factory provides a visual representation of the flow and transformation of data throughout the pipeline, helping in tracking and understanding data movements.

The REST API allows you to programmatically manage and monitor Azure Data Factory resources, such as pipelines, datasets, and activities.

Integration patterns in Azure Data Factory define how data is moved and transformed, providing flexibility and adaptability to different data integration scenarios.

Azure Data Factory supports data wrangling through the Data Flow feature, which provides a visual interface for designing and executing data transformations.

Linked services can be parameterized using dynamic content expressions, allowing for dynamic configuration based on runtime values.