9 Capital One SQL Interview Questions (Updated 2024)

At Capital One, SQL is utilized for analyzing financial data for informed decision-making. That's why Capital One almost always asks SQL questions during interviews for Data Science and Data Engineering positions.

To help you prep for the Capital One SQL interview, here's 9 Capital One SQL interview questions in this blog.

9 Capital One SQL Interview Questions

SQL Question 1: Identify Most Active Credit Card Users

Capital One, a multinational bank, wants to identify their "whale users" from the credit card usage data. A "whale user" is a customer who makes a high number of transactions, amounting to a high monetary value. Create an SQL query that analyzes the customer credit card transaction data to list down the top 10 users who have the highest total transaction amounts in the last 30 days.

Example Input:

Example Input:

Answer:

The query would look like below:

This query joins the "users" and "transactions" tables using the user_id field. It then groups the transactions made by each user in the last 30 days and calculates the total transaction amount. It also sorts users based on the total transaction amount in descending order and limits the result to the top 10 users. The output will be the list of top 10 whale users for Capital One.

To practice a similar power-user data analysis problem question on DataLemur's free interactive SQL code editor, try this recently asked Microsoft SQL interview question:

SQL Question 2: Top Department Salaries

Imagine you had a table of Capital One employee salary data. Write a SQL query to find the top 3 highest earning employees within each department.

Capital One Example Input:

Example Input:

Example Output:

Code your solution to this interview question directly within the browser on DataLemur:

Answer:

We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.

If the code above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.

I HIGHLY reccommend checking out Capital One's publication on SQL, check this one out on popular myths about relational & no-SQL Databases.

SQL Question 3: How do the 'BETWEEN' and 'IN' commands differ?

While both the and operators are used to filter data based on some criteria, selects for values within a given range, whereas for it checks if the value is in a given list of values.

For example, say you had a table called , which had the salary of the employee, along with the country in which they reside.

To find all employees who made between $80k and$120k, you could use the operator:

To find all employees that reside in the US or Canada, you could use the operator:

SQL Question 4: Analyzing Monthly Average Spending on Credit Cards

At Capital One, one of the matters that interest the bank is understanding their customers' spending habits. Let's say you're given a dataset of transactions made by credit card holders. The dataset provides the user_id, transaction amount, transaction date, and the card type.

To assist the bank in understanding their customers' behavior better, can you write a SQL query to calculate the monthly average transaction amounts for each card type from January 2022 to December 2022?

Example Input:

Example Output:

Answer:

You can use the window function in PostgreSQL to solve this SQL query.

This PostgreSQL query first extracts the month from the transaction_date and calculates the average transaction amount for each card type for each month using the AVG window function which is partitioned by card_type and month. The WHERE clause filters the transactions for the year 2022. The result is then grouped by month and card_type and ordered accordingly.

For more window function practice, solve this Uber SQL problem within DataLemur's interactive coding environment:

SQL Question 5: How does differ from just ?

The operator combines two or more results from multiple SELECT queries into a single result. If it encounters duplicate rows, the multiple copies are removed (so there's only one instance of each would-be duplicate in the result set). Here's an example of a operator which combines all rows from and (making sure each row is unique):

The operator is similar to the operator but it does NOT remove duplicate rows!

SQL Question 6: Calculating Click-through Rates

As Capital One provides digital banking service, robust analysis of click-through data is critical for the optimization of user experience and marketing strategies. Assume that Capital One tracks user activities on their app, including clicking on loan product information and subsequently applying. The click-through rate (CTR) from viewing a loan product to applying for it is the metric of interest.

Example Input:

Example Input:

We want to calculate the CTR for each product. CTR is defined as the number of users who applied for a product after clicking on it divided by the number of total unique users who clicked on the product.

Answer:

The query to accomplish this may look like:

This query left joins the table to the table using user_id and product_id as join conditions, which allows us to understand which clicks led to applications. It then groups by product_id and calculates the ratio of unique users who applied to unique users who clicked, providing the requested CTR. If a user has clicked multiple times on a product but applied only once, they will only be counted once in both the numerator and denominator.

To practice a related problem on DataLemur's free online SQL coding environment, solve this SQL interview question asked by Facebook:

SQL Question 7: Can you explain the concept of a constraint in SQL?

Think of SQL constraints like the rules of a game. Just like a game needs rules to keep things fair and fun, a database needs constraints to keep things organized and accurate.

There are several types of SQL constraints like:

NOT NULL: This constraint is like a bouncer at a nightclub - it won't let anything NULL through the door. UNIQUE: This constraint is like a VIP list - only special, one-of-a-kind values get in. PRIMARY KEY: This constraint is like an elected official - it's made up of NOT NULL and UNIQUE values and helps identify each row in the table. FOREIGN KEY: This constraint is like a diplomatic ambassador - it helps establish relationships between tables. CHECK: This constraint is like a referee - it makes sure everything follows the rules. DEFAULT: This constraint is like a backup plan - it provides a default value if no other value is specified.

So, whether you're playing a game or organizing a database, constraints are an important part of the process!

SQL Question 8: Find Customers from a Specific City

Suppose you are a Data Analyst at Capitol One and you have been assigned a task to filter out the customers who are based out of New York City. You will find the relevant data in the table.

Example Input:

Your task is to write a PostgreSQL query to retrieve a list of customers (with their ID, first name and last name) who are based out of New York.

Answer:

The SQL query will filter the table based on the city column. The keyword is used to search for a specified pattern in a column. In this case, it is used to find all customers whose city is 'New York'. Then it selects and displays the , and of these customers.

SQL Question 9: Calculate Monthly Interest Rates

Assume that Capital One has database for saving accounts and wants to calculate the monthly interest rates for accounts to better understand the financial reports. An account has a principal amount, monthly deposits, and a Yearly Interest Rate. The monthly interest is calculated as follows:

Calculate the compound value of the account after 'n' months. The table "accounts" contains: account_id (integer), principal (float), yearly_rate (float), monthly_deposit (float), months (int). After the 'n' months, the Compound Value = sum for i=0 to n: (Principal Amount + (i * Monthly Deposit)) * (1 + Yearly Rate /1200) ^ (n - i)

Note: Use the SQL functions POWER, ROUND, and arithmetic operators as required

Here's the table:

Example Input:

Example Output:

Answer:

This SQL query firstly generates a series of row for each month using the function in PostgreSQL. Then it calculates the compound value for each month and sums up all the monthly compound values using function. The result is rounded to the nearest integer using the function.

To practice a very similar question try this interactive Alibaba Compressed Mean Question which is similar for calculations involving values and frequency or this Amazon Average Review Ratings Question which is similar for requiring an average calculation over several parameters.

Capital One SQL Interview Tips

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

Each problem on DataLemur has multiple hints, detailed solutions and best of all, there's an interactive coding environment so you can easily right in the browser your SQL query and have it checked.

To prep for the Capital One SQL interview it is also useful to practice SQL questions from other payment & credit companies like:

• StoneX Group SQL questions

• American Express SQL questions

• CBRE Group SQL questions

• Blackstone SQL questions

However, if your SQL skills are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this interactive SQL tutorial.

This tutorial covers topics including GROUP BY and aggregate functions – both of these pop up routinely in Capital One interviews.

Capital One Data Science Interview Tips

What Do Capital One Data Science Interviews Cover?

In addition to SQL interview questions, the other question categories to practice for the Capital One Data Science Interview include:

• Probability & Stats Questions
• Coding Questions in Python or R
• Product Analytics Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral Based Interview Questions

How To Prepare for Capital One Data Science Interviews?

To prepare for Capital One Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from FAANG & startups
• a refresher on SQL, AB Testing & ML
• over 1000+ reviews on Amazon & 4.5-star rating