8 Kemper SQL Interview Questions (Updated 2024)

Kemper employees write SQL queries for analyzing customer risk profiles in the insurance industry, including credit scores and claims history, as well as optimizing the claims settlement process by querying large datasets, such as identifying fraudulent claims. Because of this, Kemper includes SQL problems in interviews for Data Analyst, Data Science, and BI jobs.

To help you study for the Kemper SQL interview, we'll cover 8 Kemper SQL interview questions in this blog.

8 Kemper SQL Interview Questions

SQL Question 1: Identify 'Whale' Customers for Kemper

Kemper is an insurance company. The high net-worth individuals - the ones with many expensive policies - are the ones we would consider 'Whale' customers. They are important to the business because they bring in considerable revenue. Please write a SQL query to identify customers who have more than 5 policies, each with a premium higher than $1000.

For these customers, the management wants to see all of their policies with policy_id, start_date, end_date, premium, and coverage_type. The results must be sorted by customer_id.

Example Input:

Example Input:

Answer:

This query first identifies the customer_ids that have more than 5 policies with a premium higher than $1000. Then it retrieves all the selected users' policies. The results are finally sorted by the customer_id.

To solve a related customer analytics question on DataLemur's free interactive coding environment, try this Microsoft SQL Interview problem:

SQL Question 2: 2nd Largest Salary

Imagine there was a table of Kemper employee salary data. Write a SQL query to find the 2nd highest salary among all employees.

Kemper Example Input:

Example Output:

Test your SQL query for this problem and run your code right in the browser:

Answer:

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

SQL Question 3: How does the constraint function, and in what scenarios might it be useful?

The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail.

For example, say you had a marketing analytics database that stores ad campaign data from Kemper's Google Analytics account.

Here's what some constraints could look like:

The CHECK constraint is used in the above example to make sure that the and fields contain only positive values. This helps to maintain the validity and integrity of the data in the context of ad campaigns.

The CHECK constraint can also be used to enforce other specific conditions on data. For example, you can use it to ensure that the for each ad campaign is earlier than the .

SQL Question 4: Compute Monthly Premiums

Kemper Corporation is one of America's major insurance providers. They are interested in understanding the monthly premiums each of their policyholders is paying.

Assuming we have a table named with the following data:

Example Input:

Kemper would like you to perform a query that computes the total monthly premium by month for the whole company. Each policy's monthly premium should be included in the total for each month it is active. Now, write a SQL query to get this information.

Example Output:

Answer:

For PostgreSQL, the solution is complicated because PostgreSQL doesn’t readily support the "UNNEST" function to a sequence of months. Entities like PostgreSQL's function would be very useful but they aren't always allowed in an interview environment.

Assuming we can generate a series of dates, we could use a SQL statement like this:

This query starts by generating a series of dates from the minimum start_date to the maximum end_date in the policies table. It then joins that date series with the policies table, including the policy's premium for a given month when that month and year are between the policy's start and end dates. Then, for each month and year combination, it sums the premiums of the policies that were active during that month.

Remember, availability to use certain PostgreSQL functions may vary based on interview environment or constraints.

p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Question 5: What are the ACID properties in a DBMS?

A transaction is a one or more SQL commands which are executed as a singular unit if the transaction -commits- (or no execution hapens if the transaction -aborts-).

For transactions, a DBMS is supposed to enforce the follwing ACID properties: Atomicity, Consistency, Isolation, & Durability.

Here's what each one means:

• Atomicity: the transaction is completed in an all-or-nothing way (no partial commits)
• Consistency: the transaction is valid and follows all constraints and restrictions
• Isolation: the transaction doesn't affect another transaction
• Durability: the committed transactions is stored permanently in the DB (it doesn't dissapear!)

As you can see, it's pretty important for the multiple databases where Kemper store's it's data to be ACID-compliant!

SQL Question 6: Calculate the Average Claim Amount

Kemper is a comprehensive insurance company offering auto, home, health and life insurance services. They make decisions based on averages such as average amount of insurance claims by an individual, average claim time etc. These averages give a better understanding of their customer base and determine future prospects for the company.

A potential SQL question related to Kemper could be:

"Calculate the average claim amount that was paid out for each type of insurance policy in the year 2020."

Example Input:

Example Input:

Example Output:

Answer:

This query first performs a join operation between the "claims" and "policies" tables, giving us a combined table that includes the claim amount and the type of insurance associated with each claim. It then groups this combined table by the type of insurance, and calculates the average claim amount for each type. The WHERE clause is used to only consider claims from the year 2020.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating averages or this Alibaba Compressed Mean Question which is similar for focusing on mean calculations.

SQL Question 7: Can you list the various types of joins in SQL, and describe their purposes?

Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.

In SQL, there are four distinct types of JOINs. To demonstrate each kind, Imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

• : An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.

• : A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.

• : A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.

• : A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.

SQL Question 8: Analyzing Click-Through Rates at Kemper

Kemper Corporation, a diversified insurance holding company, is interested in evaluating the click-through conversion rate of customers who view auto insurance products online then add them to their cart for purchase. The data is in two tables, and . The table contains all clicks by user, date, and product. The table contains all additions to cart by user, date, and product.

Your task: Write an SQL query that calculates the conversion rate, defined as the ratio of for each auto insurance product in the year 2023.

Example Input:

Example Input:

Answer:

In the above query, for each product, we calculate the conversion rate as the ratio of distinct users who added the product to cart after clicking on it to the total distinct users who clicked on the product. We make use of the function to only consider clicks from the year 2023.

To solve a related SQL interview question on DataLemur's free interactive SQL code editor, try this Meta SQL interview question:

How To Prepare for the Kemper SQL Interview

The best way to prepare for a Kemper SQL interview is to practice, practice, practice. Besides solving the earlier Kemper SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Meta, Google and insurance companies like Kemper.

Each SQL question has hints to guide you, step-by-step solutions and most importantly, there is an online SQL coding environment so you can right online code up your SQL query answer and have it graded.

To prep for the Kemper SQL interview it is also helpful to solve interview questions from other insurance companies like:

• Brighthouse Financial SQL questions
• Securian Financial SQL questions
• American Financial Group SQL questions
• Hanover Insurance SQL questions

Dive into Kemper's news archive and discover the latest developments shaping the insurance industry!

In case your SQL query skills are weak, don't worry about going right into solving questions – go learn SQL with this DataLemur SQL tutorial.

This tutorial covers topics including handling strings and filtering strings based on patterns – both of which pop up often in SQL job interviews at Kemper.

Kemper Data Science Interview Tips

What Do Kemper Data Science Interviews Cover?

Besides SQL interview questions, the other types of problems to prepare for the Kemper Data Science Interview are:

• Probability & Statistics Questions
• Python or R Coding Questions
• Product Data Science Interview Questions
• Machine Learning Questions
• Behavioral Interview Questions

How To Prepare for Kemper Data Science Interviews?

I believe the optimal way to prep for Kemper Data Science interviews is to read the book I wrote: Ace the Data Science Interview.

It covers 201 interview questions sourced from tech companies like Google & Microsoft. The book's also got a refresher covering Python, SQL & ML. And finally it's helped thousands of people land their dream job in data, which is why it's got over 1000+ 5-star reviews on Amazon.

While the book is more technical, it's also important to prepare for the Kemper behavioral interview. Start by reading the company's cultural values.