11 Assurant SQL Interview Questions (Updated 2024)

At Assurant, SQL is used for analyzing insurance claim patterns, including identifying fraudulent claims, as well as optimizing underwriting processes by querying and manipulating large data sets, such as policyholder information and claims data, to improve risk assessment and pricing. That is the reason why Assurant includes SQL problems in interviews for Data Science, Analytics, and & Data Engineering jobs.

To help you prep for the Assurant SQL interview, here’s 11 Assurant SQL interview questions – scroll down to start solving them!

11 Assurant SQL Interview Questions

SQL Question 1: Identify Assurant's VIP Customers

As a data engineer at Assurant, an important part of your role involves identifying and analyzing the behavior of our most valuable customers. These VIP or "whale" customers are the ones who not only buy our insurance products most frequently but also have the highest overall spending. For this task, let's focus on one product category - home insurance.

We have the following data available in our customers and purchases tables:

Example Input:

Example Input:

Your task is to write a PostgreSQL query to identify VIP customers for the Home Insurance product category. A VIP customer is defined as a customer who has made more than one purchase and whose total spending on home insurance is greater than $1500.

Answer:

Explanation:

This SQL query first joins the customers and purchases tables on the customer_id field. It then filters for purchases of the 'Home Insurance' product. Finally, it groups by the first_name and last_name of the customers and uses the HAVING clause to specify the conditions for being a VIP customer (more than one purchase and total spend greater than $1500 on home insurance). The result will be a list of VIP customers, along with the count of their purchases and the total amount they have spent.

To solve a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft SQL Interview problem:

SQL Question 2: Second Highest Salary

Imagine there was a table of Assurant employee salary data. Write a SQL query to find the 2nd highest salary at the company.

Assurant Example Input:

Example Output:

Try this question and run your code right in the browser:

Answer:

You can find a step-by-step solution here: 2nd Highest Salary.

SQL Question 3: What is denormalization?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

Denormalization is done to improve the performance of the database when it is being used for online analytics processing (OLAP), rather than online transaction processing (OLTP) use cases.

For these OLAP use cases, you're bottleneck frequently is joining multiple tables, but de-normalizing your database cuts these outs.

Denormalization can improve query performance by reducing the number of expensive joins required to retrieve data, but it comes with its own drawbacks too. By adding redundant columns, you incur more data storage costs, and there's need for more complex update and delete operations in order to maintain data integrity across all the duplicated data. Thus, it's important to carefully consider the trade-offs involved before implementing denormalization.

SQL Question 4: Calculating Monthly Average Product Ratings

Assurant offers a variety of insurance products, and they collect reviews from their customers about these products. The reviews database table records the product_id, the user_id of the reviewer, the submit_date, and the number of stars given by the user (1-5).

Write a SQL query that computes the average number of stars each product received per month. Assume that all dates are in the format "MM/DD/YYYY HH:MI:SS". Ignore years for this problem.

Example Input:

Example Output:

Answer:

This query uses PostgreSQL's function to convert the string into a timestamp. The function then pulls out the month part of that timestamp. The query groups the reviews by month and product, and for each group, it calculates the average number of stars. The result is a table that shows how users' perceptions of each product changed over time.

Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur

SQL Question 5: 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 Assurant 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.

SQL Question 6: Analysis of Insurance Policy Sales

Assurant is a global provider of risk management products and services. To better understand their policy sales, they want to analyze their data. They are particularly interested in knowing for each product category, which agent has generated the most sales, based on the policy price, within the last month.

Assume there are two tables, and . The table contains agent_id, name and other agent information, while has information about each insurance policy sold, including policy id, policy category, agent who sold it, policy price and sold date.

Example Input:

Example Input:

We need an SQL query that will give agent-wise maximum total sales for each category in the last month.

Answer:

This query first filters out policies sold in the last month. It then calculates total sales generated by each agent for each category and identifies the agent who made the maximum sales for each category.

SQL Question 7: What is database denormalization, and when is it a good idea to consider it?

Database denormalization is when you add redundancy to a database, and break typical normalization rules (specified by 1st, 2nd, 3rd normal forms). There's a few reasons to denormalize a database:

• Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases, as joins can be expensive and slow.

• Simplification: Denormalization can also be used to simplify the design of a database by reducing the number of tables and relationships that need to be managed. This can make it easier to understand and maintain the database.

• Ease of use: Denormalization can also make it easier for users to work with a database by providing them with a more intuitive and straightforward data model.

While denormalization can be a useful tool for improving performance and scalability, it's important to keep in mind that it can make update and delete operations more complex. This is because denormalization can create data duplicates, which can make it harder to maintain data integrity. So, to avoid any headaches, it's a good idea to start with a well-normalized database design and then consider denormalization only if it's absolutely necessary for your specific performance and scalability needs. In other words, denormalization can be a bit of a wild card, so it's best to handle it with care!

SQL Question 8: Filtering Customer Records

You are working as a Data Analyst at Assurant. Your task is to write a SQL query to extract customer records who purchased insurance plans after January 1, 2020, did not file any claims, and are residents of either California, Florida, or New York.

Example Input:

Answer:

This query selects all columns from the table where the purchase date is on or after January 1, 2020, the customer has not filed any claims (), and the customer is a resident of either California, Florida, or New York (). This will retrieve all records of customers who meet these conditions.

SQL Question 9: Find the Maximum Premium for Each Insurance Category

Assurant is an insurance company and they would like to review their sales data to find out the maximum premium they received for each insurance category in the last fiscal year. This will help them understand the maximum value contribution from each category.

Our database has a sales table with the following data:

Example Input:

We're asked to provide the maximum premium for each insurance category.

Question: Write a SQL query to find the highest premium paid for each insurance category in the fiscal year of 2021.

Answer:

Example Output:

This SQL statement first filters the table to include only sales in 2021. Then, it uses the GROUP BY clause to group the rows by . The aggregate function MAX is applied to each group separately, which gives the desired result of finding the maximum premium for each insurance category among the sales of 2021.

SQL Question 10: Can you explain the distinction between cross join and natural join?

Imagine you are organizing a party and have two database tables: one table of people you want to invite and another list of food items you want to serve.

A cross join would be like inviting every person on your list to the party and serving them every food item on the menu, regardless of whether they like the food or not. So, if you had 10 people on your invite list and 5 food items on the menu, you would generate all 50 different combinations of people and food (10 x 5 = 50).

On the other hand, a natural join would be like inviting only the people who like the food items on the menu (based on doing a inner/left/right/outer JOIN on a common key like ).

SQL Question 11: Filtering Customer Records With Specific Pattern

Given the customer records database, write a SQL query that finds all customers whose email addresses are '@assurant.com'. These records will be important to the business to help identify customers that could be employees or stakeholders.

Example Input:

Example Output:

Answer:

This query uses the clause with a wildcard character to filter the customers' records to only include rows where the field ends with '@assurant.com'. The '%' symbol is used in LIKE clause to represent zero, one, or multiple characters, so it matches any string that ends with '@assurant.com'.

How To Prepare for the Assurant SQL Interview

The best way to prepare for a Assurant SQL interview is to practice, practice, practice. Beyond just solving the earlier Assurant SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each problem on DataLemur has multiple hints, full answers and most importantly, there's an interactive coding environment so you can easily right in the browser your SQL query answer and have it graded.

To prep for the Assurant SQL interview it is also a great idea to practice interview questions from other insurance companies like:

• Mutual of Omaha SQL questions
• Alleghany SQL questions
• Unum Group SQL questions
• Pacific Life SQL questions

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

This tutorial covers topics including manipulating string/text data and how window functions work – both of which come up often during Assurant interviews.

Assurant Data Science Interview Tips

What Do Assurant Data Science Interviews Cover?

In addition to SQL query questions, the other question categories to practice for the Assurant Data Science Interview are:

• Probability & Stats Questions
• Coding Questions in Python or R
• Product Data Science Interview Questions
• ML Modelling Questions
• Behavioral Interview Questions

How To Prepare for Assurant Data Science Interviews?

To prepare for the Assurant Data Science interview have a firm understanding of the company's values and company principles – this will be important for acing the behavioral interview. For technical interviews get ready by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from tech companies like Netflix, Google, & Airbnb
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