9 Microsoft SQL Interview Questions (Updated 2024)

Updated on

January 17, 2024

Microsoft almost always asks SQL coding questions during interviews for Data Analyst, Data Science, and BI jobs. It's no surprise – SQL's used everywhere across the company, from analyzing Xbox player behavior to studying the health of Microsoft's fleet of servers powering Azure.

So, if you're studying for a Microsoft SQL Assessment, here’s 9 REAL Microsoft SQL interview questions to practice – how many can you solve?

Microsoft SQL Interview Questions

9 Microsoft SQL Interview Questions

SQL Question 1: Who are the top-tier users based on software purchase frequency at Microsoft?

You are a data scientist at Microsoft, and your task is to identify the power users who contribute significantly to the business by purchasing software products frequently. Write a SQL query to identify users with the highest frequency of software purchases. Top-tier or VIP users are those who have made more than 10 purchases in the last month.

Here's sample data for the problem.

Example Input:
purchase_iduser_idpurchase_dateproduct_nameproduct_price
873110508/02/2022 00:00:00Windows 11$100.00
786526508/04/2022 00:00:00Office 365$79.99
725467808/08/2022 00:00:00Visual Studio$199.99
827410508/12/2022 00:00:00Office 365$79.99
938145108/14/2022 00:00:00Windows 11$100.00
830310508/20/2022 00:00:00Visual Studio$199.99
938267808/22/2022 00:00:00Office 365$79.99
930367808/25/2022 00:00:00Windows 11$100.00
884445108/27/2022 00:00:00Office 365$79.99
975467808/30/2022 00:00:00Visual Studio$199.99
988110508/31/2022 00:00:00Windows 11$100.00

Answer:


This SQL query first filters the purchases made in the last month (August in this case). Then it GROUPS BY the results by the user_id and counts the total purchases made by each user. If the number of purchases is greater than 10, it will be included in the final result. Finally, the result is ordered in descending order to list the users with the highest number of purchases at the top. The result of this query would provide the IDs of the top-tier or VIP users who have purchased software more than 10 times in the last month.

To practice a related super-user data analysis question on DataLemur's free interactive coding environment, try this recently asked Microsoft SQL interview question:

Microsoft SQL Interview Question: Teams Super User

SQL Question 2: Mean, Median, Mode

You're given a list of numbers representing the number of emails in the inbox of Microsoft Outlook users. Before the Product Management team can start developing features related to bulk-deleting email or achieving inbox zero, they simply want to find the mean, median, and mode for the emails.

Display the output of mean, median and mode (in this order), with the mean rounded to the nearest integer. It should be assumed that there are no ties for the mode.

Table:

Column NameType
user_idinteger
email_countinteger

Example Input:

user_idemail_count
123100
234200
345300
456200
567200

Example Output:

meanmedianmode
200200200

Answer:


To try this question on our interative coding platform go here, Microsoft SQL Interview Question.

Microsoft SQL Interview Question

SQL QUESTION 3: What's denormalization, and when does it make sense to do it?

Imagine you've got giant AF jigsaw puzzle with thousands of pieces, and each piece represents a piece of data in your database. You've spent hours organizing the puzzle into neat little piles, with each pile representing a table in your database. This process is called normalization, and it's a great way to make your database efficient, flexible, and easy to maintain.

But what if you want to solve the puzzle faster(aka make your queries run faster?)?

That's where denormalization comes in – Denormalization is like the puzzle-solving equivalent of taking a shortcut!

Instead of putting all the pieces in separate piles, you might decide to clone some of the pieces, and then have that one puzzle piece be put into multiple piles. Clearly, we are breaking the rules of physics, but that's just like de-normalization because it breaks the normal rules of normalization (1st, 2nd, 3rd normal forms).

By adding redundant puzzle pieces, it can be easier to find the pieces you need, but it also means that you have to be extra careful when you're moving pieces around or adding new ones (aka INSERT/UPDATE commands become more complex).

On the plus side, denormalization can improve the performance of your database and make it easier to use. On the downside, it can make your database more prone to errors and inconsistencies, and it can be harder to update and maintain. In short, denormalization can be a helpful tool, but it's important to use it wisely!

Pro Tip: Window functions are a frequent SQL interview topic, so practice every window function problem on DataLemur

DataLemur SQL Questions

SQL Question 4: Data Storage for Microsoft’s Computer Hardware Production Details

Suppose you are working as an SQL Developer at Microsoft and you are tasked with designing a database to store information related to the company's computer hardware production. This data includes details about each hardware's type, production dates, unit cost, and the region where it was produced.

To model this scenario, we can suggest three tables: , , and .

table specifies the properties of each hardware.

Example Input:
hardware_idtypeunit_cost
1001Surface Laptop1000.00
1002Surface Pro1500.00
1003Surface Studio2500.00
1004Surface Mouse50.00
1005Surface Keyboard75.00

table holds the data of the hardware production including production date and the quantity of hardware produced.

Example Input:
production_idhardware_idproduction_datequantity
2001100106/08/2022 00:00:00200
2002100206/10/2022 00:00:00150
2003100306/14/2022 00:00:00100
2004100406/12/2022 00:00:00500
2005100506/20/2022 00:00:00400

table records where each hardware was specifically produced.

Example Input:
region_idproduction_idregion_name
30012001United States
30022002China
30032003Germany
30042004India
30052005Brazil

Now, the company wants to calculate the total cost of hardware products produced in each region in June 2022.

Answer:


This SQL query joins the , , and tables and accumulates the total production cost in each region for the given month and year by utilizing the clause. The function is used to calculate the total cost of each hardware produced, and the clause filters the data for June 2022.

SQL QUESTION 5: What's the difference between window functions and ?

As the name implies, the window function ranks each row within your window/partition. If two rows have the same rank, the next number in the ranking will be the previous rank plus the number of duplicates. For example, if you've got three records tied for 5th place, they'll get the values 5, 6, and 7, and the next row after this 3-way tie will have a rank of 8.

The function assigns a distinct rank to each row within a partition based on the provided column value with no gaps. This function will assign the same rank to two rows if they have the same rank, and give the next row the next rank number. To make this more concrete, imagine you had three records at rank 5 – then, the next rank would be 6.

RANK vs. DENSE_RANK details tutorial here: https://datalemur.com/sql-tutorial/sql-rank-dense_rank-row_number-window-function

SQL Question 6: Filtering Customer Records for Sales Analysis

As a Data Analyst at Microsoft, you are tasked with analyzing the sales performance of different software products over the years. The analysis requires you to filter out records from the 'Sales' database where the 'product_type' is 'software', the 'sales_year' is greater than 2015, and the 'sales_region' is not 'Europe'.

Example Input:

sales_idcustomer_idproduct_idproduct_typesales_yearsales_regionunits_sold
1AB123S1001Software2022North America150
2AD768S1002Hardware2021Europe65
3AB123S1003Software2020Asia200
4BD672S1001Software2016Europe100
5CD980S1003Software2015North America80
6AB123S1002Software2022Europe120
7AD768S1001Software2019Asia85

Example Output:

sales_idcustomer_idproduct_idproduct_typesales_yearsales_regionunits_sold
1AB123S1001Software2022North America150
3AB123S1003Software2020Asia200
7AD768S1001Software2019Asia85

Answer:


This query filters the 'Sales' table based on the mentioned conditions. It selects all fields for the records where the 'product_type' is 'Software', the 'sales_year' is greater than 2015, and the sales did not occur in the 'Europe' region.

SQL QUESTION 7: What's a primary key?

A primary key is a column or set of columns in a table that uniquely identifies each row in the table. The primary key is used to enforce the uniqueness and non-nullability of the rows in the table.

In a SQL database, a primary key is defined using the constraint. For example, say you had a table of :


In this example, the column is the primary key of the Microsoft employees table. It is defined as an integer and is marked as the primary key using the constraint.

A table can have only one primary key, but the primary key can consist of multiple columns. For example, say you had a table of Microsoft customer transactions:


In the above example, the primary key of the Orders table consists of two columns: TransactionID and ProductID. This means that the combination of OrderID and ProductID must be unique for every row in the table.

SQL Question 8: Analyzing Click-Through and Conversion Rates for Microsoft Digital Products

Microsoft wants to analyze the click-through rates of their digital ads and the conversion rates from viewing a product page to adding the product to the shopping cart, across different product categories. They are specifically interested in their popular categories: 'Software', 'Games', 'Hardware', and 'Services'.

To accomplish this, they provided you with two tables, 'clicks' and 'conversions', containing the following data:

Example Input:
click_iduser_idclick_dateproduct_idproduct_category
110106/01/2022 00:00:00001Software
210206/02/2022 00:00:00002Games
310306/03/2022 00:00:00003Hardware
410106/04/2022 00:00:00004Services
510206/05/2022 00:00:00005Services
Example Input:
conversion_iduser_idconversion_dateproduct_id
90110106/01/2022 00:00:00001
90210206/02/2022 00:00:00002
90310106/01/2022 00:00:00001
90410106/04/2022 00:00:00004

Write a SQL query to calculate both the click-through rates (ratio of clicks to total unique users) and conversion rates (ratio of users who add the product to the shopping cart to total unique users viewed the product) for each product category, for the month of June 2022.

Answer:

Here is the SQL query that achieves this:


The above query first creates two subqueries: one for click rates and another for conversion rates, where each subquery counts the distinct number of users who clicked/viewed and converted for each product category, respectively. The final query then merges these rates, calculates the click-through and conversion rates by dividing by total unique users who clicked or converted, and fills in zero for any categories where there were no conversions.

To solve a related problem on DataLemur's free interactive SQL code editor, attempt this Meta SQL interview question: SQL interview question asked by Facebook

SQL Question 9: Filter customer records matching specific pattern

Microsoft HR team often tracks the progress and performance of its employees. Each employee is classified into different departments based on their job description. However, recently a lot of employees have joined departments that are related to Artificial Intelligence. As a database officer, you are asked to filter the employee records for any department that includes the word 'AI' in its description.

Example Input:
emp_idfirst_namelast_nameemailjob_description
3521JohnSmithjohnsmith@microsoft.comSoftware Engineer - AI
4678JaneDoejanedoe@microsoft.comProduct Manager - AI
5732MikeJonesmikejones@microsoft.comData Analyst
8391EmmaWilliamsemmawilliams@microsoft.comAI Research Scientist
5347BobJohnsonbobjohnson@microsoft.comNetwork Engineer
Example Output:
emp_idfirst_namelast_nameemailjob_description
3521JohnSmithjohnsmith@microsoft.comSoftware Engineer - AI
4678JaneDoejanedoe@microsoft.comProduct Manager - AI
8391EmmaWilliamsemmawilliams@microsoft.comAI Research Scientist

Answer:


In this SQL query, '%' is a wildcard character that matches any sequence of characters. So, 'AI' captures anything that includes 'AI' anywhere in the 'job_description' field. Therefore, the given query returns all records from the 'employees' table where the job description contains 'AI'. Here, it returns the records of employees who work in departments related to Artificial Intelligence.

Microsoft SQL Interview Tips

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Microsoft SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the above Microsoft SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Microsoft, Google, Amazon, and tech startups. DataLemur Question Bank

Each exercise has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there's an online SQL coding environment so you can instantly run your query and have it checked.

To prep for the Microsoft SQL interview you can also be a great idea to solve SQL questions from other tech companies like:

In case your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.

DataLemur SQL tutorial

This tutorial covers things like math functions and sorting results with ORDER BY – both of these show up frequently in Microsoft SQL interviews.

Microsoft Data Science Interview Tips

What Do Microsoft Data Science Interviews Cover?

For the Microsoft Data Science Interview, beyond writing SQL queries, the other types of questions which are covered:

  • Probability & Statistics Questions
  • Python or R Programming Questions
  • Product Analytics Questions
  • ML Modelling Questions
  • Behavioral Interview Questions

For a more in-depth understanding, read the Microsoft Data Science Interview Guide which has 25+ real Microsoft questions, and covers everything from the interview process including the Machine Learning and Python Questions!

How To Prepare for Microsoft Data Science Interviews?

Besides practicing on DataLemur, the best way to prepare for Microsoft Data Science interviews is by reading Ace the Data Science Interview. The book's got:

  • 201 Interview Questions from FAANG, and some from Microsoft too!
  • A Refresher covering SQL, AB Testing & ML
  • Great Reviews (900+ 5-star reviews on Amazon)

Ace the Data Science Interview by Nick Singh Kevin Huo

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