10 Mercury General SQL Interview Questions (Updated 2024)

Data Scientists, Analysts, and Data Engineers at Mercury General write SQL queries almost every for analyzing policyholder data, including demographic and behavioral data, for risk prediction models. It is also used for managing policy databases, such as updating policy information and tracking customer interactions, for efficient customer service, the reason why Mercury General asks interviewees SSQL coding interview questions.

So, to help you practice, here’s 10 Mercury General SQL interview questions – can you answer each one?

10 Mercury General SQL Interview Questions

SQL Question 1: Analyzing Claims Data

Mercury General is an automobile insurance company. Suppose that they want to analyze their data to understand how claims payments are changing over time at a department level. They have a table with records of every claim submitted by each department. Each record contains the , the , the , and the paid for the claim.

The question is, "Write a SQL query to calculate the total claim payments and average payment per claim submitted by each department in each year, and rank the departments by total payment each year."

Example Input:

Answer:

This query first groups the claims by department and year, calculating the total and average claim amount for each group. The final SELECT statement then applies a window function to rank the departments within each year based on the total claim amount. The result will be a list of departments ranked by total claim amount for each year, along with the total and average claim amounts. This information can help the company identify which departments handle the most costly insurance claims and how this changes over time.

To solve another window function question on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question:

SQL Question 2: Top Three Salaries

Suppose you had a table of Mercury General employee salary data. Write a SQL query to find the top three highest paid employees in each department.

Mercury General Example Input:

Example Input:

Example Output:

Try this interview question interactively 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 solution above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.

SQL Question 3: What does it mean to use a constraint in a database?

The constraint makes sure that all values in a column are distinct. It is often paired with other constraints, like NOT NULL, to ensure that the data follows certain rules.

For example, say you were an analyst on the marketing team at Mercury General, and had access to a database on marketing campaigns:

In this example, the UNIQUE constraint is applied to the "campaign_name" field to ensure that each campaign has a unique name. This helps to ensure the integrity of the data in the table and prevents errors that could occur if two campaigns had the same name.

SQL Question 4: Filter Customer Records Based on Multiple Conditions

As part of the data analytics team in Mercury General, your task is to analyze the customer database and provide a list of active registered customers living in 'California' or 'New York' but not holding any 'Auto insurance'.

For this task, you have been provided with the 'Customers' table which presents you with the details of customers.

Example Input:

Example Output:

Answer:

The PostgreSQL query for this question is:

In our given example, the query filters out the customers who are living in either 'California' or 'New York' and are active but do not have 'Auto insurance'. This sort of query can be particularly useful for finding specific subsets of customers who might be interested in particular offers, or who might be targets for specific marketing campaigns.

SQL Question 5: What are the three different normal forms?

Normal forms are guidelines that are used to help design a relational database in a way that minimizes redundancy and ensures the integrity of the data. The 3 most commonly use normal forms are the 1st, 2nd, and 3rd normal forms. Here's a brief explanation of each:

• 1st Normal Form (1NF) is all about keeping it simple - each column should only have one value and there should be no repeating groups of data.

• 2nd Normal Form (2NF) is about organization - your database should already be in 1NF and all the non-key columns should depend on the primary key. This means that each non-key column should be completely dependent on the entire primary key, not just part of it.

• 3rd Normal Form (3NF) is about independence - if your database is already in 2NF, then all the non-key columns should not depend on each other. They should be self-sufficient and not rely on other non-key columns.

SQL Question 6: Calculate the Click-Through Rate (CTR)

Mercury General, a motor vehicle insurance company, has recently been running multiple digital ad campaigns. They want to understand the Click-through rate (CTR) of these campaigns, especially the ads that prompt clients to get a quote for their vehicles.

The dataset includes:

• Ad impressions which is the number of times the ad was shown to potential clients i.e., table
• Ad clicks which is the number of times potential clients clicked on the ad to get a quote i.e., table

We'd like to calculate the Click-through rate (CTR) which is the percentage of ad impressions that led to clicks.

Example Input:

Example Input:

Answer:

This query starts by joining the and tables on . It then counts the unique and for each , and divides one by the other to calculate the Click-Through Rate (CTR). The clause is used to calculate these metrics for each individual ad campaign.

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

SQL Question 7: Could you describe a self-join and provide a scenario in which it would be used?

A self-join is a type of join in which a table is joined to itself. To perform a self-join, you need to specify the table name twice in the FROM clause, and give each instance of the table a different alias. You can then join the two instances of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

Self-joins are the go-to technique for any data analysis that involves pairs of the same thing, like identifying pairs of products that are frequently purchased together like in this Walmart SQL interview question.

For another example, say you were doing an HR analytics project and needed to analyze how much all Mercury General employees in the same department interact with each other. Here's a self-join query you could use to retrieve all pairs of Mercury General employees who work in the same department:

This query returns all pairs of Mercury General employees who work in the same department, and excludes pairs where the employee's id is the same (since this would represent the same Mercury General employee being paired with themselves).

SQL Question 8: Retrieve Customer Details From Certain City

Mercury General is in the insurance industry, and they prioritize serving customers according to their city of residence. For a newly launched marketing campaign, they want you to retrieve the details of all customers who live in a city that starts with 'San'.

Here are the example table below:

Example Input:

We need to write an SQL query that filters out records of customers that reside in cities starting with 'San'.

Answer:

This query selects all columns from the table where the column starts with 'San'. The ‘%’ symbol is a wildcard in SQL that matches any number of characters. This is how we can find records where the city starts with 'San' like 'San Francisco', 'San Diego', etc.

After executing the query, you will get only the customer details which are from a city that starts with 'San'.

SQL Question 9: Analyze and Combine Customer and Policy Tables

Given a dataset of Customers which includes their personal details and a dataset of Policies bought by these customers, write a SQL query to identify:

1. The total number of distinct customers who have purchased at least one policy
2. Total unique policies bought by customers
3. Total number of policies bought per state

For the purpose of this analysis, consider the table and :

Example Input:

Example Input:

Answer:

This query starts by joining the and tables on the . The clause groups the result by state, customer_id and policy_number. The function returns the number of distinct values of the specified column. The function with clause gives us the total number of policies bought per state.

Since joins come up routinely during SQL interviews, take a stab at this interactive Snapchat SQL Interview question using JOINS:

SQL Question 10: Can you explain the difference between a foreign and primary key in a database?

To explain the difference between a primary key and foreign key, let's start with an example Mercury General sales database:

:

In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.

and could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.

How To Prepare for the Mercury General SQL Interview

The best way to prepare for a Mercury General SQL interview is to practice, practice, practice. Besides solving the above Mercury General SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each DataLemur SQL question has multiple hints, full answers and best of all, there is an interactive coding environment so you can right in the browser run your SQL query and have it checked.

To prep for the Mercury General SQL interview you can also be wise to practice SQL problems from other insurance companies like:

• Ventas SQL questions
• TruStage SQL questions
• Kemper SQL questions
• Brighthouse Financial SQL questions

Stay ahead of the financial curve with Mercury Financial's latest news and updates!

This tutorial covers things like Union vs. UNION ALL and LEAD/LAG – both of which pop up routinely during Mercury General SQL interviews.

Mercury General Data Science Interview Tips

What Do Mercury General Data Science Interviews Cover?

Beyond writing SQL queries, the other question categories covered in the Mercury General Data Science Interview include:

• Statistics and Probability Questions
• Python Pandas or R Coding Questions
• Product Analytics Questions
• Machine Learning Questions
• Behavioral Based Interview Questions

How To Prepare for Mercury General Data Science Interviews?

I believe the best way to prepare for Mercury General Data Science interviews is to read the book Ace the Data Science Interview.

It covers 201 data interview questions taken from FAANG, tech startups, and Wall Street. The book's also got a refresher on Python, SQL & ML. And finally it's helped thousands of people land their dream job in data, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.

While the book is more technical, it's also key to prepare for the Mercury General behavioral interview. A good place to start is by understanding the company's culture and values.