Microsoft’s Azure Data Factory is a cloud service for transforming chaotic data into usable insights. It’s a data integration service that can extract, transform, and load information without human intervention.
Engineers working with Azure Data, as well as businesses that need to move data, can greatly benefit from using Azure Data Factory. The ability to work with and understand ADF is essential for any data engineer.
Here, we’ll take a look at real-time scenarios of interview questions that could come up in an interview for a position at Azure Data Factory, as well as some sample questions that might be asked.
In this blog, we will be discussing –
- Azure Data Factory Job Interview Questions For Freshers
- Azure Data Factory Interview Questions for Seasoned Professionals
- Interview Questions for Azure Data Factory Real-Time Scenarios
To succeed in your next interview, practice with these Azure Data Factory interview questions and answers.
Azure Data Factory Interview Questions For Freshers
Q1. In order to execute an SSIS package in Data Factory, what is required?
The SSIS integration runtime and SSISDB catalog must be established in an Azure SQL server database or an Azure SQL-managed instance before an SSIS package can be executed.
Q2. How do you define the Azure Data Factory?
Microsoft’s Azure Data Factory is a fully managed, serverless, cloud-based ETL and data integration service. Either “extract-transform-load” (ETL) or “extract-load-transform” (ELT) is employed when moving large amounts of data from one repository to another, most frequently a data lake or data warehouse. It lets you make and run data pipelines to help move and change data, as well as run pipelines on a schedule.
Q3: Is Azure Data Factory an ETL tool?
It’s a Microsoft cloud service that makes it easier to combine large amounts of data for analysis. It also works with the ETL and ELT paradigms.
Q4. Why do we require the ADF?
A service like ADF is required to coordinate and run the processes that transform massive amounts of raw business data into actionable business insights as the volume of big data continues to increase.
Q5. What is the purpose of Azure Data Factory’s linked services?
There are two main applications for linked services in Data Factory:
For a representation of data kept in a Data Store, such as an Oracle Database or SQL Server database, an Azure Blob storage account, or a file system.
For Compute representation, i.e., the VM that is running in the background will carry out the activity defined in the pipeline.
Azure Data Factory Interview Questions For Experienced Professionals
Experts in the field must be familiar with its capabilities and operation. Take a look at some of the top interview questions about Azure Data Factory that experienced professionals have been asked in the past. You can prepare for your next job interview with this knowledge of what to expect from employers.
Q1. What exactly does the term “Azure Table Storage” mean?
The Azure Table Storage service provides users with the ability to store structured data in the cloud. In addition to this, it features a keystore that contains schemas and offers users assistance in arranging their data. In today’s fast-paced and demanding environments, it functions admirably and efficiently.
Q2: Is it possible for an administrator to manage and monitor Azure Data Factory pipelines?
The following procedures can be used to manage ADF pipelines and ensure that they are properly tracked:
- To access this feature, go to the Data Factory menu, and then select “Monitor and Manage.”
- Proceed by selecting “Resource Manager” now.
- Pipelines, datasets, and connected services are all displayed in a tree structure.
Q3. An Azure Data Factory pipeline can be executed in one of three different ways. Mention these methods.
The following are the execution methods for Azure Data Factory pipelines:
- Debugging Attempts
- Lever-based lethal injections are being used now
- By incorporating a timer, a sliding window/event trigger, and a tumbling window/event trigger, we can:
Q4. Which integration runtime should be used when copying data from a local instance of SQL Server to a data factory?
It is recommended that the self-hosted integration runtime be installed on the local machine that serves as the hosting location for the SQL Server instance.
Q5. Can you take me through the various stages of the ETL process?
The following are the four primary steps that make up the Extract, Transform, and Load process, also known as ETL.
- Connect and Collect is a feature that assists in the movement of data to local storage and stores it with the assistance of the crowd. Modify the data by utilizing services such as HDInsight, Hadoop, and Spark, among others.
- Publish: Provides assistance when loading data into Azure data warehouses, Azure SQL databases, Azure Cosmos DB, and other Azure storage options.
- Monitor – Provides support for Azure Monitor, as well as API, PowerShell, log analysis, and pipeline monitoring via the Azure portal’s health scope.
Also Read:
Azure Data Lake: How to Harness Big Data for Intelligent Decision-making
Interview Questions for Azure Data Factory Real-Time Scenarios
It is important, when preparing for an interview for a job in the Azure Data Factory, to know what kinds of real-life situations you might face on the job. These kinds of situations can be found in the job description. Interviewers often use scenario-based questions to assess your problem-solving skills and Azure Data Factory knowledge.
Let’s start with some of the most common scenario-based Azure Data Factory interview questions.
- Imagine being a data engineer for a company.. The company wanted to move its on-premises cloud to Microsoft’s cloud. This will likely be done with the Azure data factory. Data from one on-premises table was transferred to Azure via a pipeline. To run this pipeline successfully, what steps do you need to take?
- Imagine you’re a data engineer at ABC. You did well facilitating movement. In the place you’re changing, this works fine. Would you put this pipeline into production without changing it?
- Imagine you have around a terabyte (TB) of information stored in Azure’s blob service. Depending on the specifics of your business, you may be asked to make a few adjustments to this information before committing it to the staging container. Detail your explanation.
- Assume you have activated an Internet of Things device The car’s device communicates with Microsoft Azure’s blob storage once an hour to back up the information. Wherever it is, you must transfer these records to an SQL database immediately. abase. How would you go about creating the fix? Give reasons for the same.
- Let’s say you’re studying COVID data from around the world. This data is available via REST API from some public forums. How would you fix this?
Conclusion
The demand for Azure data engineers is high, and the supply is plentiful. And as more and more businesses move to the cloud in the coming years, demand for these workers is only expected to rise. However, success depends entirely on how well you’ve been preparing for such chances.
With this list, you’ll have access to the most frequently asked and hardest Azure Data Factory interview questions. Use these Azure Data Factory-specific interview questions to give yourself an edge over other candidates.
