Top 15 Azure Data Factory Interview Questions and Answers (2022)

Azure Data Factory is one of the most powerful cloud-based Microsoft tools. It gathers business data and processes it in order to provide usable insights and information. Data Factory is an extract-transform-load (ETL) service that automates data transformation.
Here are the top Azure Data Factory interview questions that you should know before going to a job interview. You should be familiar with Azure Data Factory if you want to advance your career in Microsoft Azure. These questions and answers will help you understand the basics of Microsoft Azure.
Most frequently asked questions and answers about the Azure Data Factory interview:
These interview questions and answers for Azure Data Factory are prepared by industry professionals who have over 7-15 years of experience in an Azure data factory.
Let’s get started! !
Q1. Q1. What are the components in Azure Data Factory? Please explain.
Pipeline: This is a list of all activities that occur within a logical container.
Dataset:Datasets point to data that is used in pipeline activities.
Mapping Data Flow is a UI logic for data transformation.
Activity:In Data Factory pipelines this refers to executions that you can use to transform and consume data.
Trigger: A trigger is a way to determine the pipeline execution time.
Linked Service: This is a connection string that allows data sources to be used in pipeline activities.
Control Flow: This regulates the execution flow of pipeline activities.
Q2. Why do we need Azure Data Factory?
You will find Data Factory mentioned in every Microsoft Azure tutorial. Data flows through many sources in today’s data-driven world. Each source can channel or transfer data using different methods and formats. This information must be efficiently managed before it can be shared over the cloud or other storage platforms. This means that raw data from multiple sources must be cleaned, filtered, and transformed before it can be shared, with any unwanted components removed.
This is about data transfer. Enterprises should ensure that data is gathered from multiple sources, and stored in a single location. Data storage and transformation can be achieved using traditional warehouses. They do have some limitations. For managing their processes, conventional warehouses use customised applications. This is a time-consuming task and it can be difficult to integrate all processes. You need a way to automate or ensure that workflows are properly designed. All these processes can be easily coordinated with Azure Data Factory.
Q3. Q3. What is the limit to the number of integration runtimes you can perform, if any?
Azure Data Factory allows you to perform unlimited integration runtime incidents. There is no limit to what you can do in the Azure Data Factory. There is however, a limit.