10 Gallagher US SQL Interview Questions (Updated 2024)

Data Science, Data Engineering and Data Analytics employees at Gallagher US uses SQL to extract and analyze insurance data from databases for risk assessments, including policyholder profiling and risk segmentation. It is also used for automating data-related tasks for increased business efficiency, such as streamlining policy underwriting, which is why Gallagher US asks prospective hires SQL coding interview questions.

To help you ace the Gallagher US SQL interview, here’s 10 Arthur J. Gallagher SQL interview questions in this blog.

10 Arthur J. Gallagher SQL Interview Questions

SQL Question 1: Finding Power Users for Gallagher US

Considering Gallagher US as an insurance company, an important activity users might do is filing insurance claims. You might consider a "Power User" to be someone who files a significant number of claims, suggesting they are making the most use of their insurance policies.

Your task is to write a SQL query which analyzes the customer database, finding users who have filed more than 10 claims in the past year (2022). Additionally, for the users identified, provide the total sum of their claims.

Here are some sample tables:

Example Table:

Example Table:

Answer:

This PostgreSQL query would identify users who have filed more than 10 claims in the year 2022 and will output their user_id, user_name, the number of claims they have (claim_count), and the total amount of their claims (total_claim_amount). This is accomplished by JOINing the user and claims tables on the user_id columns, and then grouping the results by user_id and user_name. The HAVING clause is then used to filter out any users who have not filed at least 10 claims.

To practice a super-customer analysis question on DataLemur's free interactive coding environment, try this Microsoft Azure Cloud SQL Interview Question:

SQL Question 2: Department vs. Company Salary

You're given a table of Gallagher US employee and department salary information. Write a SQL query to find departments where the departments average salary is higher than the company's average salary.

You can solve this question and run your code right in DataLemur's online SQL environment:

The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department Salaries.

SQL Question 3: What are the similarities and difference between relational and NoSQL databases?

While both types of databases are used to store data (no duh!), relational databases and non-relational (also known as NoSQL databases) differ in a few important ways:

Data model: Relational databases use a data model consisting of tables and rows, while NoSQL databases use a variety of data models, including document, key-value, columnar, and graph storage formats.

Data integrity: Relational databases use structured query language (SQL) and enforce strict data integrity rules through the use of foreign keys and transactions. NoSQL databases may not use SQL and may have more relaxed data integrity rules.

Structure: Relational databases store data in a fixed, structured format, while NoSQL databases allow for more flexibility in terms of data structure.

ACID compliance: Relational databases are typically into shrooms and are ACID-compliant (atomic, consistent, isolated, and durable), while NoSQL databases may not be fully ACID-compliant (but they try their best... and it's effort that counts...or at least that's what my gym teacher told me!)

SQL Question 4: Sales Performance Evaluation

As the company's data analyst, you have been asked to analyze Gallagher’s insurance policy sales data. The task requires you to identify the top 3 sales agents for every month over the past year who had the highest total sales.

Here is the sample data for the past year:

Example Input:

Expected Output:

Answer:

To solve this task, you can use the SQL Window function in PostgreSQL. Here is an example answer:

This SQL query will firstly group sales data by month, year and agent, calculating total sales for each. The Window function is then applied to rank agents within each month and year group, ordered by the value of their total sales. By practicing with HAVING clause we filter out to only include the top 3 sales agents each month.

The final result will not include agents ranked below third within each month. This allows us to identify our top-performing sales agents on a monthly basis.

To solve a similar window function question on DataLemur's free interactive coding environment, solve this Google SQL Interview Question:

SQL Question 5: Can you describe the difference between a clustered and a non-clustered index?

Here's an example of a clustered index on the column of a table of Gallagher US payments table:

This creates a clustered index on the column, which will determine the physical order of the data rows in the table.

Here is an example of a non-clustered index on the column of the same table:

This will create a non-clustered index on the column, which will not affect the physical order of the data rows in the table.

In terms of query performance, a clustered index is usually faster for searches that return a large number of records, while a non-clustered index is faster for searches that return a small number of records. However, updates to a clustered index are slower, as they require the data rows to be physically rearranged, while updates to a non-clustered index are faster, as they only require the index data structure to be updated.

SQL Question 6: Insurance Claim Analysis

Gallagher US is an insurance brokerage providing commercial insurance, risk management, and consulting services. One of their main goals is to manage risk effectively for their clients. They are interested in understanding the trend in the number and total value of insurance claims submitted each month.

They have two main tables in their database:

1. table, where each row represents a client with their respective personal details. The primary key of the table is .

2. table, where each row represents an insurance claim submitted by a client. This table has a foreign key that references the table.

Given these, please design the and database schemas and write a SQL query to perform the following actions:

1. For each month, calculate the total number of claims submitted.
2. Calculate the total value of these claims.

Your query should return these statistics sorted by month.

Example Input:

Example Input:

Answer:

This query groups the table by month, then counts the total number of claims and sums the total value of the claims for each month. It returns these statistics in ascending order of month. The function is used to truncate the to month, which enables us to group by month.

SQL Question 7: What are database views, and when would you use them?

Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're just like a regular table?

Views are useful for creating a simplified version of your data for specific users, or for hiding sensitive data from certain users while still allowing them to access other data.

SQL Question 8: Filter Customer Data Based on Specific Criteria

In the Gallagher US customer database, we want to filter out certain customers. We're interested in customers who are in the 'CA' state, have a credit score of more than 750, and their insurance coverage type is 'Premium' or 'Platinum'. For cases with these specific conditions, return their Customer ID, Full Name, State, Credit Score, and Insurance Coverage Type.

Sample input data:

Example Input:

Example output:

Expected Output:

Answer:

A PostgreSQL query to solve the above problem is:

This query filters out customers who are located in California state, have a credit score greater than 750, and who have either 'Premium' or 'Platinum' as their insurance coverage type. It returns the customer_id, full_name, state, credit_score, and coverage_type for those specific customers.

SQL Question 9: Average Number of Insurance Claims Per Client

Gallagher US is an insurance brokerage and risk management services firm. They might ask you to provide the average number of insurance claims each client has made within a particular year.

For example, you need to create SQL script to find out the average number of insurance claims for each client during 2023.

Example Input:

Example Input:

Answer:

With the above SQL script, a subquery is created to count the number of claims per client within the year of 2023. This is then joined with the clients table to get the average count of claims per client. The AVG function here calculates the average number of claims for all the clients.

To practice a very similar question try this interactive Twitter Histogram of Tweets Question which is similar for requiring a count by individual or this LinkedIn Duplicate Job Listings Question which is similar for needing to count duplicate occurrences.

SQL Question 10: Why is normalizing a database helpful?

Database normalization is a good idea to implement because it can reduce redundancy which can improve performance and database flexibility.

By dividing larger tables into smaller, more modular and specific tables which are linked via foreign keys, this can usually improve the speed of some queries because it minimizes the amount of random data the query has to sift through. However, it's not always 100% true that there is a query speed-up, because joins are an expensive operation.

Nonetheless, by reducing redundancy, besides improved performance you also get more database flexibility. By making tables more modular and reducing overlap, you're able to more easily, since one table can be changed more effortlessly without affecting others. This makes it easier to adapt the database schema to Gallagher US's evolving business needs.

Gallagher US SQL Interview Tips

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Gallagher US SQL interview is to solve as many practice SQL interview questions as you can! Besides solving the earlier Gallagher US SQL interview questions, you should also solve the 200+ DataLemur interview questions 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's an online SQL coding environment so you can right in the browser run your SQL query answer and have it graded.

To prep for the Gallagher US SQL interview it is also useful to solve SQL questions from other insurance companies like:

• FM Global SQL questions
• First American Financial SQL questions
• Old Republic SQL questions
• American Tower SQL questions

Dive into Gallagher US’ news archive and explore the latest developments shaping the insurance industry!

But if your SQL query skills are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers things like sorting results with ORDER BY and 4 types of JOINS – both of which pop up routinely in Gallagher US interviews.

Arthur J. Gallagher Data Science Interview Tips

What Do Gallagher US Data Science Interviews Cover?

Beyond writing SQL queries, the other types of problems covered in the Gallagher US Data Science Interview include:

• AB Testing & Experimentation Questions
• Python or R Programming Questions
• Product Metrics Interview Questions
• Machine Learning Questions
• Behavioral Interview Questions focussed on Gallagher US values & principles

How To Prepare for Gallagher US Data Science Interviews?

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

• 201 interview questions taken from Facebook, Google & startups
• a crash course on Stats, SQL & ML
• over 1000+ 5-star reviews on Amazon

Don't forget about the behavioral interview – prepare for that using this list of common Data Scientist behavioral interview questions.