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Top Azure Data Factory Interview Questions and Answers

02/Dec/2021 | 10 minutes to read


Here is a List of essential Azure Data Factory Interview Questions and Answers for Freshers and mid level of Experienced Professionals. All answers for these Azure Data Factory questions are explained in a simple and easiest way. These basic, advanced and latest Azure Data Factory questions will help you to clear your next Job interview.

Azure Data Factory Interview Questions

Azure Data Factory Interview Questions and Answers

These questions are targeted for Azure Data Factory which is an essential part of Azure Cloud. Azure Developers must know the answers of these frequently asked Azure Data Factory interview questions to clear the interview. In short it's known as ADF.

1. What is Azure Data Factory?

Azure Data Factory is a serverless, fully managed data integration service. It provides the capability to integrate different data sources with more than 90 built-in connectors which are maintenance free at no extra cost. It allows you to create ETL and ELT processes in a code free environment or gives an option to write your own code. For more visit Azure Data Factory and if you are new to Azure Data Factory then visit Data Factory Documentation.

2. What are the Pipelines and Activities in Azure Data Factory?

A data factory consists of one or more pipelines. A Pipeline is a logical set of activities that together perform some action. For example, A pipeline can have activities which ingest the data into File Share and publish some event once the task is completed. A Pipeline allows you to manage the activities as a set instead of each one. A data factory allows you to deploy and schedule the pipeline instead of each activity individually.
Activity refers to some actions that you need to perform on data. For example, you can use copy activity to transfer data from Azure Blob Storage to Azure File Share. Data factory groups the activities into three categories as below.
  • Data movement activities
  • Data transformation activities
  • Control activities
For more visit Pipelines and Activities.

3. Explain Linked services in Azure Data Factory (ADF)?

Linked service allows you to link your data store to a data factory. It is similar to connection strings that defines a connection information for a data factory to connect external data sources. For example, An Azure storage linked service can define the connection to link Azure storage to a data factory. For more visit Azure Data factory Linked Services.

Azure Data Factory Related Other Interview Questions:

4. What are Datasets in ADF?

Dataset refers to that data that you are going to use in your pipeline activities as inputs and outputs. Dataset represents the structure of data within linked data stores such as files, folders, documents etc. For example, An Azure blob dataset defines the container and folder in blob storage from which a pipeline activity should read data as input to process. For more visit Datasets.

5. Explain Integration Runtime in the Data Factory?

Azure data factory uses a compute infrastructure known as Integration Runtime (IR), Which provides data integration capabilities over different network environments. These integration capabilities include:
  • Data Flow
  • Data Movement
  • Activity Dispatch
  • SSIS package execution
For more visit Integration Runtime.

6. How does ADF Pipeline execution work?

A pipeline run can be defined as an instance of a pipeline execution. For example, you have a data factory pipeline to copy data from blob to file share that runs by event grid trigger. Each pipeline run has a unique id known as pipeline run id. This pipeline run id is a GUID that uniquely identifies each pipeline run. You can run a pipeline either by using some trigger or manually. For more visit Pipeline Execution.

7. What are Triggers in a Data Factory?

Triggers represent an action or unit of processing which determines when a pipeline execution can be kicked off. Triggers are another way to execute a data factory pipeline. Triggers have many-to-many relationships with pipelines meaning - a single trigger can kick off multiple pipelines, or multiple triggers can kick off a single pipeline execution. Azure Data factory supports three types of triggers as below.
  • Schedule trigger
  • Tumbling window trigger
  • Event-based trigger
For more visit Triggers.

8. Explain Data flows in Azure Data Factory.

9. How to create Azure Data Factory?

10. How to create Azure Data Factory Data Flow?

11. How will you secure your Azure Data Factory?

12. What are the Azure Data Factory Naming rules?

13. Explain data redundancy in Azure Data Factory.

14. Explain Templates in Azure Data Factory.

15. What is Control flow in Azure Data factory?

16. How to schedule a pipeline run?

17. Can I pass parameters to the Data factory Pipeline?

Yes, you can pass the parameters in the data factory pipeline. You can define parameters at pipeline level and pass the arguments when trigger the pipeline execution by using trigger or on demand.

18. Can I define default values for parameters in pipeline?

Yes, you can define default values for parameters.

19. Can an activity consume arguments which are passed to a pipeline run?

Yes, you can use pipeline parameter value inside an activity using @parameter construct.

20. Can an activity output property consumed in another activity?

Yes, you can use one activity output in subsequent activity using @activity construct.

21. How to handle null values in an activity output?

You can handle null values in an activity output using @coalesce construct in the expressions.

22. How to create an event based trigger to run a pipeline?

23. How will you plan and manage costs for Azure Data Factory?

24. How will you plan and manage costs for Azure Data Factory?

Some General Interview Questions for Azure Data Factory

1. How much will you rate yourself in Azure Data Factory?

When you attend an interview, Interviewer may ask you to rate yourself in a specific Technology like Azure Data Factory, So It's depend on your knowledge and work experience in Azure Data Factory.

2. What challenges did you face while working on Azure Data Factory?

This question may be specific to your technology and completely depends on your past work experience. So you need to just explain the challenges you faced related to Azure Data Factory in your Project.

3. What was your role in the last Project related to Azure Data Factory?

It's based on your role and responsibilities assigned to you and what functionality you implemented using Azure Data Factory in your project. This question is generally asked in every interview.

4. How much experience do you have in Azure Data Factory?

Here you can tell about your overall work experience on Azure Data Factory.

5. Have you done any Azure Data Factory Certification or Training?

It depends on the candidate whether you have done any Azure Data Factory training or certification. Certifications or training are not essential but good to have.


We have covered some frequently asked Azure Data Factory Interview Questions and Answers to help you for your Interview. All these Essential Azure Data Factory Interview Questions are targeted for mid level of experienced Professionals and freshers.
While attending any Azure Data Factory Interview if you face any difficulty to answer any question please write to us at Our IT Expert team will find the best answer and will update on the portal. In case we find any new Azure Data Factory questions, we will update the same here.