11 CNO Financial Group SQL Interview Questions (Updated 2024)
At CNO Financial Group, SQL is used for analyzing customer data, including demographic and behavioral data, to generate risk assessment models, as well as retrieving specific datasets for financial forecasting, including projecting revenue and identifying areas for cost reduction. That is why CNO Financial Group asks SQL questions in interviews for Data Science, Analytics, and Data Engineering jobs.
Thus, to help you study for the CNO Financial Group SQL interview, we've collected 11 CNO Financial Group SQL interview questions – can you solve them?
11 CNO Financial Group SQL Interview Questions
SQL Question 1: Identify VIP Customers for CNO Financial Group
"CNO Financial Group" primarily deals with insurance policies (life insurance, health insurance, etc.) for its customers. In this context, a 'VIP customer' could be considered as one who holds multiple policies and has been a customer for a long period of time.
Write a SQL query to identify customers who have purchased more than 2 policy types and have been a customer for more than three years. For these 'VIP customers', also display the total number of policies they hold and the length of their relationship with the company in years.
Example Input:
| customer_id | customer_name | policy_start_date |
|---|---|---|
| 811 | John Doe | 01/01/2015 |
| 927 | Jane Smith | 21/04/2016 |
| 634 | Mary Johnson | 05/08/2018 |
| 932 | James Williams | 27/12/2019 |
| 127 | Patricia Brown | 03/02/2017 |
Example Input:
| policy_id | customer_id | policy_type |
|---|---|---|
| 3011 | 811 | Life Insurance |
| 3027 | 811 | Health Insurance |
| 3255 | 927 | Life Insurance |
| 3582 | 634 | Health Insurance |
| 3648 | 811 | Auto Insurance |
| 3981 | 927 | Health Insurance |
Answer:
The above query begins by joining the and tables on the field. It then groups the results by and . The clause filters for customers who hold more than two policy types and for whom more than 3 years have passed since the . The function is used to calculate the total number of policies each customer holds, and the function is used to determine the length of each customer's relationship with the company in years.
To solve a related customer analytics question on DataLemur's free interactive coding environment, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: Department Salaries
Assume you had a table of CNO Financial Group employee salary data, along with which department they belonged to. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
Try this interview question and run your code right in DataLemur's online SQL environment:
The answer is LONG – 30+ lines of SQL. You can find a detailed solution with hints here: Department Salaries.
SQL Question 3: How do cross joins and natural joins differ?
Cross join and natural join are like two sides of a coin in the world of SQL.
Cross joins is like the wild and reckless cousin who creates a giant new table by combining every row from table A with every row from table B, no questions asked, no common key needed.
Natural joins are like the more refined and selective cousin who only combines rows from multiple tables if they have something in common (i.e., common columns/keys).
While cross join doesn't discriminate and will create a massive table if given the chance, natural join is more selective and only returns a table with the number of rows equal to the number of matching rows in the input tables. So, choose your JOIN wisely!
SQL Question 4: Ranking Agents by Total Policy Sales
CNO Financial Group sells various financial products to its customers, which are primarily handled by agents. Assuming each agent is managing several policies, the firm is interested in knowing the performance of these agents in terms of total policy sales made by them each month.
Write a SQL query to generate a report that lists each agent, the total number of policies they sold in every month, and their monthly rank according to the number of policies sold. Ranking should be done in descending order, i.e., the agent with the highest sales should rank 1.
Example Input:
| policy_id | policy_start_date | agent_id | product_id | sale_amount |
|---|---|---|---|---|
| 001 | 06/05/2022 | 450 | 2315 | $100 |
| 002 | 06/10/2022 | 678 | 5321 | $200 |
| 003 | 06/20/2022 | 450 | 2315 | $150 |
| 004 | 07/02/2022 | 678 | 5321 | $180 |
| 005 | 07/15/2022 | 123 | 8965 | $400 |
| 006 | 07/30/2022 | 678 | 5321 | $300 |
Example Output:
| month | agent_id | total_sale | rank |
|---|---|---|---|
| 06 | 450 | $250 | 1 |
| 06 | 678 | $200 | 2 |
| 07 | 678 | $480 | 1 |
| 07 | 123 | $400 | 2 |
Answer:
This SQL statement uses the window function to generate a ranking based on the total sale amount for each agent within each month. The clause is used to specify that we want a separate ranking for each month, and the clause is used to sort the ranking in descending order of total sales. The 'RANK()' function then provides a unique rank to each agent, with 1 being the highest (best sales). The results are grouped by month and agent, then ordered by month and rank to make the output easier to read.
To practice a related window function SQL problem on DataLemur's free online SQL coding environment, try this Google SQL Interview Question:
SQL Question 5: What does the clause do vs. the clause?
Before we address vs. question, let's address the clause which is used in a statement to group rows into a set of summary rows. It's typically used in conjunction with aggregate functions such as:
- `MIN
The clause is used to filter the groups created by the clause. It's similar to the clause, but it is used to specify conditions on the groups created by the clause, rather than on the individual rows of the table.
For example:
This query retrieves the total salary for each department and groups the rows by department. The clause then filters the groups to include only CNO Financial Group departments where the total salary is greater than $1 million
Note that the clause must be used after the clause and can only reference columns listed in the clause or aggregated columns selected by the statement.
SQL Question 6: Average Premium Amount of Policies
Given a database of insurance policies sold by CNO Financial Group, can you find the average premium amount for each insurance type?
Please use the data from the "policies" table with the following structure:
Example Input:
| policy_id | customer_id | start_date | insurance_type | premium_amount |
|---|---|---|---|---|
| A101 | 901 | 01/06/2022 | Life Insurance | 200 |
| B102 | 711 | 01/04/2022 | Health Insurance | 500 |
| A103 | 501 | 01/02/2022 | Life Insurance | 350 |
| D104 | 402 | 01/01/2022 | Auto Insurance | 180 |
| D105 | 333 | 01/04/2022 | Auto Insurance | 220 |
Answer:
You can find the average premium amount for each insurance type by grouping the policies data by the insurance type and then applying the AVG function on the premium amount. Here's the PostgreSQL query for finding the solution:
This query first groups the data in the policies table by the field. Then, for each group, it calculates the average value of the . This average represents the average premium amount for each type of insurance that CNO Financial Group provides.
The output of this query should indicate the average premium for each type of insurance. This data could be used for business analysis, such as identifying which insurance type brings in the most revenue or comparing the pricing structure to market standards.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for requesting average calculations on grouped data or this Alibaba Compressed Mean Question which is similar for calculating the mean from a table.
SQL Question 7: Can you explain the concept of a constraint in SQL?
In a database, constraints are rules that the DBMS (database management system) follows when performing operations such as inserting, updating, or deleting data.
For example, consider a table of employee records at CNO Financial Group. Some constraints that you might want to implement include:
- NOT NULL: This constraint ensures that certain columns, such as the employee's first and last name, cannot be NULL.
- UNIQUE: This constraint ensures that each employee has a unique employee ID.
- PRIMARY KEY: This constraint combines the NOT NULL and UNIQUE constraints to create a primary key for the employee table. The primary key is a column or set of columns that uniquely identifies each row in the table.
- FOREIGN KEY: This constraint establishes a relationship between the employee table and other tables in the database. For example, you could use a foreign key to link the employee ID to the department ID in a department table to track which department each employee belongs to.
- DEFAULT: This constraint specifies a default value for a column in case no value is specified when a new row is inserted into the table.
SQL Question 8: Calculate the click-through-rate (CTR) for the Insurance Products
CNO Financial Group, a company that provides a range of insurance products, has recently launched an online ad campaign to attract potential customers. The marketing team has placed ads on various digital platforms like search engines and social media sites and has been collecting data regarding user interactions. Each time a user sees an ad it's considered an impression, and if the user clicks on the ad it's marked as a click.
Now, the marketing team wants to evaluate the performance of their ad campaign by calculating the click-through rate (CTR). CTR measures the ratio of users who click on a specific link to the number of total users who view the ad (impressions).
To calculate CTR, you need to divide the number of clicks by the number of impressions and then multiply the result by 100 to get the percentage.
You are given two tables, and , with the following fields:
Example Input
| impression_id | ad_id | impression_date |
|---|---|---|
| 111 | 1 | 08/01/2022 |
| 222 | 1 | 08/01/2022 |
| 333 | 1 | 08/01/2022 |
| 444 | 2 | 08/01/2022 |
| 555 | 2 | 08/01/2022 |
Example Input
| click_id | ad_id | click_date |
|---|---|---|
| 101 | 1 | 08/01/2022 |
| 102 | 1 | 08/01/2022 |
| 103 | 2 | 08/01/2022 |
| 104 | 3 | 08/01/2022 |
Answer:
This SQL query firstly groups the tables by then for each ad, it counts the number of unique impressions and clicks. These counts are used to calculate the CTR. Using a left join ensures that ads with 0 clicks are still included in the final result.
To practice a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's interactive coding environment:
SQL Question 9: Find Customers' Information for Insurance Policies Sold By Agents Named as 'John'
The CNO Financial Group stores its customer data in the table and the insurance policy sales data in the table. Each insurance agent at the company has a unique , and the name of every agent is stored in the table.
You need to write a SQL query to find out all the customer information for those who have purchased an insurance policy from an agent named 'John'.
Example Input:
| customer_id | first_name | last_name | phone | |
|---|---|---|---|---|
| 0545 | Brad | Pitt | bradpitt@email.com | 4545454545 |
| 6789 | Angelina | Jolie | ajolie@email.com | 5678567856 |
| 8910 | Oscar | Grant | ogrant@email.com | 7890789078 |
Example Input:
| sale_id | agent_id | customer_id | policy_id | sale_date |
|---|---|---|---|---|
| 9456 | 001 | 0545 | SLI325 | 01/05/2021 |
| 3568 | 002 | 6789 | HLI890 | 07/03/2021 |
| 7198 | 001 | 8910 | PLI230 | 10/06/2021 |
Example Input:
| agent_id | agent_name |
|---|---|
| 001 | John |
| 002 | David |
You need to consider the for 'John' in the table. If the matches the in the sales table, include the customer's information in the output.
Answer:
This query combines the data from all three tables. In the clause, it connects the , , and tables based on the and . The clause then filters the results to include only those where the is 'John'.
SQL Question 10: Can you explain the concept of database normalization?
Normalizing a database involves dividing a large table into smaller and more specialized ones, and establishing relationships between them using foreign keys. This reduces repetition, resulting in a database that is more adaptable, scalable, and easy to maintain. Additionally, it helps to preserve the accuracy of the data by reducing the likelihood of inconsistencies and problems.
SQL Question 11: Analyze Customer's Policy Enrollment
CNO Financial Group wants to analyze their customer's policy enrollment. They have two tables, and . The table contains customer details such as . The table contains policy enrollment details for customers .
Write a SQL query to list all customers along with the policies they have enrolled, order by customer's name in ascending order and issue date in descending order.
Example Input:
| id | name | dob |
|---|---|---|
| 1 | John Doe | 1972-07-18 |
| 2 | Jane Smith | 1985-12-03 |
| 3 | James Johnson | 1990-02-21 |
Example Input:
| policy_id | customer_id | policy_type | issue_date |
|---|---|---|---|
| 101 | 1 | Auto Insurance | 2018-07-18 |
| 102 | 1 | Life Insurance | 2020-03-18 |
| 103 | 2 | Health Insurance | 2019-05-10 |
| 104 | 3 | Auto Insurance | 2018-08-12 |
Example Output:
| name | dob | policy_type | issue_date |
|---|---|---|---|
| John Doe | 1972-07-18 | Life Insurance | 2020-03-18 |
| John Doe | 1972-07-18 | Auto Insurance | 2018-07-18 |
| Jane Smith | 1985-12-03 | Health Insurance | 2019-05-10 |
| James Johnson | 1990-02-21 | Auto Insurance | 2018-08-12 |
Answer:
This SQL query will join the table with the table on the basis of and . The resulting data is then ordered based on in ascending order and in descending order.
Because joins come up so often during SQL interviews, practice this Snapchat JOIN SQL interview question:
How To Prepare for the CNO Financial Group SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews. Besides solving the above CNO Financial Group SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.
Each DataLemur SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there's an interactive SQL code editor so you can right in the browser run your SQL query answer and have it executed.
To prep for the CNO Financial Group SQL interview it is also useful to solve interview questions from other insurance companies like:
- CNO Financial Group SQL questions
- Voya SQL questions
- American National SQL questions
- Digital Realty Trust SQL questions
Explore the latest happenings at CNO Financial Group and stay ahead of the curve!
In case your SQL foundations are weak, forget about jumping right into solving questions – improve your SQL foundations with this interactive SQL tutorial.
This tutorial covers SQL topics like filtering strings using LIKE and different types of joins – both of which come up routinely in CNO Financial Group SQL assessments.
CNO Financial Group Data Science Interview Tips
What Do CNO Financial Group Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions covered in the CNO Financial Group Data Science Interview include:
- AB Testing Questions
- Python Pandas or R Coding Questions
- Business Sense and Product-Sense Questions
- Machine Learning Questions
- Behavioral Questions focussed on CNO Financial Group values & principles
How To Prepare for CNO Financial Group Data Science Interviews?
To prepare for CNO Financial Group Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from FAANG & startups
- a crash course on Stats, ML, & Data Case Studies
- over 1000+ 5-star reviews on Amazon
Don't ignore the behavioral interview – prep for that using this list of common Data Scientist behavioral interview questions.