11 Globe Life SQL Interview Questions (Updated 2024)

Globe Life employees use SQL for extracting and analyzing customer data, including policy details and claims history, to predict future trends, as well as maintaining and optimizing data pipelines for efficient data management, like streamlining data processing workflows. This is the reason why Globe Life asks SQL questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.

So, to help you prepare for the Globe Life SQL interview, we've curated 11 Globe Life SQL interview questions – can you solve them?

11 Globe Life SQL Interview Questions

SQL Question 1: Identify Power Users for Globe Life

For a company like Globe Life, which is a direct marketing firm offering life and health insurance products, a power user could be identified as a policyholder who frequently interacts with the company. This could either be through regular payments, frequent viewing of policy information online, participating in wellness programs, etc. In this scenario, let's identify power users as those who have frequently made payments.

Here's the problem posed as a SQL question:

Problem: With the company's database of insurance policy payments, write a SQL query to identify power users who made payments more than a certain threshold (let's say ten times) within a specific period (let's say one year, from 2020).

Example Input:

Answer:

Here's a query to identify the power users:

The query returns the user_id and payments_count of power users. This is done by filtering records between the specified date range, grouping the data by user_id and retaining only those users who have a payment_count greater than the defined threshold. The result is then sorted in descending order of payment counts.

This query will provide Globe Life a list of high engagement users to focus on for potential up-selling or loyalty programs.

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: Top 3 Salaries

Given a table of Globe Life employee salary information, write a SQL query to find the top 3 highest paid employees in each department.

Globe Life Example Input:

Example Input:

Example Output:

Test your SQL query for this question and run your code right in DataLemur's online SQL environment:

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 detailed solution with hints here: Top 3 Department Salaries.

SQL Question 3: What does do?

The function accepts an unlimited number of input arguments, and returns the first argument from that list which isn't null.If all input arguments are null, will return null too.

For example, suppose you had data on Globe Life salespeople, and the amount of deals they closed. This data was exported from a 3rd-party system CRM, which exports a value if the salesperson didn't close any deals.

To get rid of these NULLs, and replace them with zero's (so you can do some further analytics like find the average number of closed deals), you would use the function as follows:

You'd get the following output:

SQL Question 4: Calculating Monthly Premium Frequencies

Globe Life is a provider of life and health insurance products. They are interested in understanding their policy sales in more detail. They have a 'sales' table where each row represents a policy sold. You have been asked to write a SQL query to find out the total number of policies sold each month for each type of insurance product, with the calculation of cumulative policies sold in each month.

The table has the following schema:

Example Input:

The expected query result should show the total number of each type of insurance policy sold month by month as well as the running total.

Example Output:

Answer:

In this query, PostgreSQL's window functions are used to calculate the monthly sales and cumulative sales figures for each product type. The clause segments the data into categories for each product type and month-year, and ensures that the data is served in the desired order.

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

SQL Question 5: How does an inner join differ from a full outer join?

An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.

For example, suppose you had a table of Globe Life orders and Globe Life customers.

INNER JOIN: When there is a match in the shared key or keys, rows from both tables are retrieved. In this example, an between the Orders and Customers tables would retrieve rows where the in the Orders table matches the in the Customers table.

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

SQL Question 6: Analysis of Life Insurance Policies

The company Globe Life specializes in providing insurance products. They want to explore their existing data and learn more about the distribution of life policies among different states, policy types, and age groups of holders. Specifically, they're interested in understanding how many active policies there are for each age group, state, and policy type. These insights will help them tailor their offerings and make strategic decisions. {#Question-6}

Given two tables, and , which capture details about the policy holders and the specific policies they've taken out respectively, can you help answer this question?

Example Input:

Example Input:

Answer:

Here is a PostgreSQL query to solve this problem:

Writeup

This query works by joining the and tables based on the column. It then groups the results based on , , and . It uses the function to count the number of active policies for each group. The result is a summary of the distribution of active policies.

SQL Question 7: What does do, and when would you use this SQL command?

The SQL command merges the results of multiple statements and keeps only those rows that are present in all sets.

For example, say you were doing an HR Analytics project for Globe Life, and had access to Globe Life's employees and contractors data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who also show up in the employees table:

SQL Question 8: Filter Customer Records for Specific Insurance Policies

As a data analyst at Globe Life, you're tasked to filter the customer records database to find out customers who have either 'term life' or 'whole life' insurance policies, aged between 30 and 40 years, and live in 'Texas'. It is important to also exclude all customers whose insurance policies are already expired.

Here are the tables providing the necessary information.

Example Input:

Example Input:

Answer:

This SQL query first uses a JOIN operation to combine data from and tables where the matches. Then it applies the WHERE clause to filter out rows based on the given conditions: (1) policy is either 'Term Life' or 'Whole Life'; (2) customer's age is between 30 and 40 as of the end of 2022; (3) customer's state is 'Texas; and (4) policy end date is later than end of 2022.

SQL Question 9: Find Average Insurance Premium for Different Age Groups

Globe Life sells various types of insurance policies and maintains a record of each customer's age and the amount of premium they pay. Write an SQL query that groups customers into buckets based on age - Under 30, 30 to 50, and over 50 - and calculates the average insurance premium amount for each group.

Example Input:

Example Input:

Example Output:

Answer:

This query first creates a subquery or CTE named which assigns an age group to each age in the table. This CTE is then joined with the table on the column. Finally, the query groups by and calculates the average for each age group.

SQL Question 10: What are the similarities and differences between the and functions?

Both window functions are used to find rows at a given offset from the current row. However, will give you the rows AFTER the current row you. On the other hand, will give you the rows BEFORE the current row.

SQL Question 11: Filter Customers Information

As a part of data analysis at Globe Life, you often have to deal with customer information. Assume that Globe Life is interested to know how many of its customers are from Texas (assume Texas can be found in their addresses), also locating the individuals who have 'John' as part of their full name. Write an SQL query to filter such customer information which meets the two mentioned conditions simultaneously.

Let's consider the following sample database for the above problem:

Example Input:

Answer:

Your query should look something like this:

This query will return all records from the 'customers' table where the 'full_name' contains 'John' and the 'address' contains 'Texas'. '' is a wildcard in SQL that matches any number of characters. This way, it doesn't matter where 'John' or 'Texas' appears in the text fields, and we can still locate the relevant rows.

Preparing For The Globe Life SQL Interview

The key to acing a Globe Life SQL interview is to practice, practice, and then practice some more! In addition to solving the above Globe Life SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Google, Facebook, Microsoft and Amazon.

Each DataLemur SQL question has hints to guide you, full answers and most importantly, there is an interactive SQL code editor so you can instantly run your SQL query and have it graded.

To prep for the Globe Life SQL interview it is also wise to practice SQL problems from other insurance companies like:

• Securian Financial SQL questions
• Kemper SQL questions
• Brighthouse Financial SQL questions
• Securian Financial SQL questions

Explore the latest updates from Globe Life and discover how they're innovating in the insurance space!

In case your SQL coding skills are weak, forget about jumping right into solving questions – strengthen your SQL foundations with this free SQL tutorial.

This tutorial covers things like WHERE vs. HAVING and Self-Joins – both of these show up often during Globe Life interviews.

Globe Life Data Science Interview Tips

What Do Globe Life Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions to practice for the Globe Life Data Science Interview include:

• Statistics and Probability Questions
• Python or R Programming Questions
• Product Analytics Questions
• ML Modelling Questions
• Behavioral Questions based on Globe Life cultural values

How To Prepare for Globe Life Data Science Interviews?

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

• 201 interview questions sourced from FAANG (FB, Apple, Amazon, Netflix, Google)
• a refresher on Stats, ML, & Data Case Studies
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Also focus on the behavioral interview – prep for that using this guide on acing behavioral interviews.