Azure Data Factory Interview Questions And Answers
A Comprehensive Guide to Azure Data Factory Interview Questions and Answers
Azure Data Factory Interview Questions And Answers
In an Azure Data Factory interview, candidates can expect questions that assess their understanding of data integration concepts, ETL processes, data transformation techniques, data movement, and monitoring capabilities within the Azure Data Factory platform. Common interview questions may include discussing how to create pipelines, manage triggers, use data flows, handle errors, and optimize performance within Azure Data Factory. To succeed in such interviews, candidates should be prepared to showcase their knowledge of various features and functionalities of Azure Data Factory, demonstrate problem-solving skills, and provide examples of past project experiences related to data integration and orchestration.
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1 - What is Azure Data Factory (ADF)?
Azure Data Factory is a cloud based data integration service that allows you to create, schedule, and manage data pipelines for ETL (Extract, Transform, Load) and data integration workflows.
2) What are the key components of Azure Data Factory?
The key components of Azure Data Factory include datasets, linked services, pipelines, activities, triggers, and integration runtimes.
3) What is a dataset in Azure Data Factory?
A dataset represents the data structure within the data store and is used to define the schema and structure of the data that will be used in the data pipelines.
4) What is a linked service in Azure Data Factory?
Linked services are used to link and connect external data sources and destinations to Azure Data Factory and provide the information needed to connect to these data stores.
5) What is a pipeline in Azure Data Factory?
A pipeline in Azure Data Factory is a logical grouping of activities that together perform a specific task, such as moving data from a source to a destination.
6) What are activities in Azure Data Factory?
Activities are the processing steps within a pipeline that define the actions to be performed on the data, such as copying data, transforming data, or executing external scripts.
7) What is a trigger in Azure Data Factory?
Triggers are used to define the runtime properties of when a pipeline should be executed, based on a schedule or an external event.
8) What is an integration runtime in Azure Data Factory?
Integration runtimes provide the compute infrastructure needed to execute data movement and data transformation activities within Azure Data Factory.
9) How can you monitor and manage Azure Data Factory pipelines?
You can monitor and manage Azure Data Factory pipelines using the Azure portal, Azure Monitor, and Azure Data Factory's built in monitoring features, which provide logs and metrics to track the performance of your data pipelines.
10) How does Azure Data Factory support data movement and transformation?
Azure Data Factory supports data movement and transformation through a variety of built in connectors, data flows, and activities that allow you to ingest, process, and transform data from various sources and destinations in a scalable and efficient manner.
These are just a few common Azure Data Factory interview questions along with their answers that can help you prepare for your interview.
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