Top 11 Azure Data Services Interview Questions in 2023

Introduction

In today’s world, data is growing exponentially with time with digitalization. Organizations are using various cloud platforms like Azure, GCP, etc., to store and analyze this data to get valuable business insights from it. You will study top 11 azure interview questions in this article which will discuss different data services like Azure Cosmos DB, Azure SQL Database, Azure Data Lake Storage, etc., for storing structured, unstructured, or semi-structured data. Let’s take a look at the below azure interview questions.

Learning Objectives

In this article, we will learn about the below azure interview questions:

1. Scope of Azure Data Services job profiles
2. Important Cosmos DB concepts
3. Cosmos DB offers different database APIs
4. Understand deployment models provided by Azure SQL Database
5. Learn about lifecycle policy rules in Azure Blob Storage
6. Gain knowledge about Azure Storage Data services

This article was published as a part of the Data Science Blogathon.

Table of Contents

1. Q1. Which Companies are Hiring for the Job Profiles Related to Azure Data Services?
2. Q2. What are Request Units in Cosmos DB?
3. Q3. What is Time to Live in Cosmos DB?
4. Q4. What are the Different Database APIs Offered by Cosmos DB? Elaborate with Examples.
5. Q5. Describe the Purchasing Models Available in Azure SQL Database.
6. Q6. What are the Different Deployment Models Provided by Azure SQL Database?
7. Q7. Scenario-based Question on Azure Data Lake.
8. Q8. What are the Azure Storage Data Services?
9. Q9. Scenario-based Question on Azure Blob Storage.
10. Q10. Write a Query to Create Table Depts in the CompanyDB Azure SQL Database.
11. Q11. Which Azure Service Should you Choose for Developing an Enterprise Data Lake to Perform Big Data Analytics?
12. Conclusion

Top companies like Mercedes-Benz, Deloitte, PwC, Accenture, TCS, Razorpay, Swiggy, Uber, etc., are hiring for job profiles related to Azure Data Services skills such as Data Engineer, Data Scientist, R&D-related data roles, etc. at various locations across the world. These job profiles have a wide scope in terms of salary, getting challenging work environments, and solving real-world problems. A working professional requires intensive knowledge of Azure SQL, Azure Data Lake development, developing APIs using Cosmos DB as a database, creating data pipelines using Azure Data Factory, etc., to work in this job.

Q2. What are Request Units in Cosmos DB?

The request unit is a performance currency that abstracts the system resources required to perform the database operations like read, insert, update, etc., supported by Azure Cosmos DB. Consumed Request Units get charged depending upon the Azure Cosmos DB account creation mode.

Q3. What is Time to Live in Cosmos DB?

Time to Live (TTL) in Cosmos DB allows automatically deleting items inside a container after a certain time period by consuming left-over Request Units. Example of configuring TTL in existing Cosmos DB Container:

Select Container-> in settings scroll to Time to Live-> select On and specify TTL value in seconds-> Save.

Q4. What are the Different Database APIs Offered by Cosmos DB? Elaborate with Examples.

Azure Cosmos DB offers various database APIs like MongoDB, Cassandra, Gremlin, NoSQL, and Table. Azure Cosmos DB API for NoSQL provides the option to query items using SQL syntax and offers performance isolation and analytical support. Azure Cosmos DB API for MongoDB provides multiple write locations, automatic shard management, and stores data in document structure using BSON format. Azure Cosmos DB for PostgreSQL is used for storing data in PostgreSQL. Azure Cosmos DB API for Cassandra supports horizontal scaling to store extensive data using column-oriented schema. Example of creating a database school using Azure Cosmos DB API for NoSQL in .NET:

Database database1 = await client.CreateDatabaseAsync( id: "school" ) 

For example, insert a single document in the collection named student using Azure Cosmos DB API for MongoDB in JavaScript:

db.student.insertOne({   name:"Chaitanya Shah",   age: 23,   address: "24, Wall Colony" });

Q5. Describe the Purchasing Models Available in Azure SQL Database.

Depending on the deployment model of Azure SQL Database, below are the two purchasing models available:

a. vCore Purchasing Model: The vCore purchasing model allows the users to choose hardware physical characteristics based on their application needs. In this model, customers can independently choose to scale storage, compute resources, etc.

b. DTU-based Purchasing Model: Database Transaction Unit (DTU)–based purchase model provides customers service tiers that are differentiated based on the fixed compute size, storage, read-write rates, and retention period for back-ups.

Q6. What are the Different Deployment Models Provided by Azure SQL Database?

Below are the two deployment models provided by Azure SQL Database:

a. Single Database: Single database type deployment model creates a database with a dedicated database engine, its own set of resources, performance monitoring, and service tiers.

b. Elastic Pool: Elastic pool type deployment model enables the customers to purchase resources for a pool shared by multiple databases. We can add or remove databases from the pool based on resource utilization. An elastic pool solves the problem of resource overprovisioning and under-provisioning.

Q7. Scenario-based Question on Azure Data Lake.

While working on project ABC, you created an Azure Data Lake Storage Gen2 account abc_account for storing application and infrastructure logs. The designated retention period for storing application and infrastructure logs is 360 days and 60 days, respectively. As per the current expectations, the logs will not be accessed during the retention periods. Design a solution for the abc_account that will minimize storage costs and automatically delete the logs at the end of each retention period.

Use the archive access tier to store application logs and the cool access tier to store infrastructure logs to minimize the storage costs while storing logs in abc_account. For automatically deleting the logs at the end of each retention period, use Azure Blob storage lifecycle management rules.

Q8. What are the Azure Storage Data Services?

Azure Storage Service provides highly scalable, accessible, secure, and managed services to store objects, blob, create data
lakes, file sharing, etc. Below are the Azure Storage Data services:

• Azure Blobs: Azure Blob storage allows users to store unstructured data using blobs. Azure Blob storage can be used to store log files, images, documents, data for backup and restore, etc.
• Azure Files: Azure Files allow users to share files using industry standards such as SMB, NFS, etc. Azure Files can be used to store debugging and development tools needed by VMs.
• Azure Queues: Azure Queue storage is a messaging service for storing a large number of messages. Azure Queue can be used for asynchronous messaging communication between application components.
• Azure Tables: Azure Tables allow users to store structured NoSQL data with a schema-less design. Azure Tables can be used to store address books, device information, etc.
• Azure Disks: Azure Disks are used for storing and accessing data from Azure VMs.

Q9. Scenario-based Question on Azure Blob Storage.

Write the lifecycle policy rule in Azure Blob Storage to transition the block blobs prefixed with container/school or container/college that haven’t been modified in 90 days to the archive tier and blobs not modified over 30 days cool storage tier.

Below is the lifecycle policy rule for the above scenario:

{ "rules": [ { "name": "agingPolicy", "enabled": true, "type": "Lifecycle", "definition": { "filters": { "blobTypes": [ "blockBlob"], "prefixMatch": [ " container/school ", " container/college " ] }, "actions": { "baseBlob": { "tierToCool": { "daysAfterModificationGreaterThan": 30 }, "tierToArchive": { "daysAfterModificationGreaterThan": 90 } } } } } ]
}

Q10. Write a Query to Create Table Depts in the CompanyDB Azure SQL Database.

The below query will create a table named Depts with the columns DeptNo, DName, and Location:

CREATE TABLE Depts(
DeptNo int Primary Key,
DName nvarchar(50) NOT NULL,
Location nvarchar(50)
);

Here, DeptNo is Primary Key.

Q11. Which Azure Service Should you Choose for Developing an Enterprise Data Lake to Perform Big Data Analytics?

You should use Azure Blob storage to create a data lake for big data analytics. Azure Blob storage allows users to store
unstructured data using blobs. Azure Blob storage provides high security, scalability, data availability, and disaster-recovery capabilities.

Conclusion

Microsoft Azure offers data services like Azure Cosmos DB, Azure SQL Database, Azure Data Lake Storage, etc. for storing structured, unstructured, or semi-structured data. Azure Cosmos DB is a multi-model, fully managed, NoSQL database for modern application development. Azure Storage Service provides highly scalable, accessible, secure, and managed services to store objects, blob, create data lakes, file sharing, etc. Below are some important points from the above article on azure interview questions:

• Azure Cosmos DB offers various database APIs like MongoDB, Cassandra, Gremlin, NoSQL, and Table for connecting to different databases.
• Using Time to Live (TTL) in Azure Cosmos DB, developers can automatically delete items inside a container.
• Elastic pools in Azure SQL Database can help organizations use shared resources for Azure SQL.
• We got an understanding of which Azure Storage Data service should be used based on the scenario and data type.
• Apart from this, we have also seen the Azure Storage access tiers and lifecycle management policies.

I hope you liked my article on azure interview questions. Share your feedback with me in the comments section.

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