9 Microsoft SQL Interview Questions (Updated 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?

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:

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:

SQL Question 2: Calculate Monthly Average of Product Ratings With Window Function

Suppose that Microsoft wants to understand customer satisfaction with various products. As part of this analysis, you have been tasked to calculate a monthly average of product ratings provided by customers.

You have been given access to a table in Microsoft's SQL Server Database, with the following schema:

Example Input:

The submit_date column is in 'YYYY-MM-DD' format. Your task is to write a SQL query that calculates the monthly average star rating for each product.

Provide an output in the following format:

Example Output:

Answer:

Using the window function in SQL, we can get the average rating per month for each product.

Here is the SQL query that can be used to calculate the monthly average star rating per product.

In this query, we use the MONTH function to extract the month from the submit_date column. We then use the AVG function (which is a window function since it's used with the OVER clause) to calculate the monthly average rating for each product. The PARTITION BY clause is used to specify the groups (i.e., months and products) for which we want to calculate the monthly average ratings. Finally, we use the ORDER BY clause to make the result set easier to analyze.

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

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

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:

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

Example Input:

table records where each hardware was specifically produced.

Example Input:

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:

Example Output:

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:

Example Input:

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 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:

Example Output:

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.

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:

• Apple SQL questions

• Google SQL questions

• Amazon SQL questions

• Oracle SQL questions

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.

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

How To Prepare for Microsoft Data Science Interviews?

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)