11 State Farm SQL Interview Questions (Updated 2024)

State Farm employees write SQL queries to analyze claim data for suspicious patterns and anomalies that may indicate insurance fraud. It is also used to structure customer data to create personalized insurance product recommendations based on their coverage needs and risk profiles. For this reason, State Farm includes SQL problems during interviews for Data Science, Data Engineering and Data Analytics jobs.

So, to help you study, we've curated 11 State Farm Insurance SQL interview questions – able to answer them all?

11 State Farm Insurance SQL Interview Questions

SQL Question 1: Identify the "Power Users" of State Farm Insurance Services

State Farm is a large insurance and financial services company. Its business depends on a wide range of users who apply for its insurance policies and use other services. A "Power User" or "VIP User" for State Farm might be defined as a user who has multiple active policies and who regularly makes payments, thus demonstrating both a wide use of services and consistent financially beneficial behavior for the company.

Using the hypothetical tables , , and as shown:

Table:

Table:

Table:

Answer:

To identify the Power Users, we will look for users who have multiple active policies and make regular payments. The SQL query to solve this is:

This SQL query joins the 'users', 'policies', and 'payments' tables on the user_id field, filters out the policies that are not active, and then groups by user_id and user_name. It selects only those users having more than one unique policy and more than one unique payment, meaning they have multiple active policies and have made multiple payments. The output is ordered by the number of policies and then the number of payments, both in descending order, thus giving us a list of "Power Users" for State Farm.

To practice a similar customer analytics SQL question where you can code right in the browser and have your SQL solution automatically checked, try this Walmart Labs SQL Interview Question:

SQL Question 2: Top Three Salaries

Imagine you had a table of State Farm employee salary data. Write a SQL query to find the top 3 highest paid employees within each department.

State Farm Example Input:

Example Input:

Example Output:

Test your SQL query for this problem interactively on DataLemur:

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 code above is tough, you can find a step-by-step solution here: Top 3 Department Salaries.

SQL Question 3: What is a database index, and what are the different types of indexes?

An index in a database is a data structure that helps to quickly find and access specific records in a table.

For example, if you had a database of State Farm customers, you could create a primary index on the column.

Having a primary index on the column can speed up performance in several ways. For example, if you want to retrieve a specific customer record based on their , the database can use the primary index to quickly locate and retrieve the desired record. The primary index acts like a map, allowing the database to quickly find the location of the desired record without having to search through the entire table.

Additionally, a primary index can also be used to enforce the uniqueness of the column, ensuring that no duplicate values are inserted into the table. This can help to prevent errors and maintain the integrity of the data in the table.

SQL Question 4: Calculate average premiums per state

would like to calculate the average car insurance premium per state every month. We have a table, where each row is a policy, and it includes the following columns: (integer), (integer), (string), (timestamp), (timestamp), (float). Can you write a SQL query to return the average premium per state each month? Exclude any policies that have ended before the month you're calculating for.

Example Input:

Example Output:

Answer:

We use the window function to calculate the average premium, partitioned by the state and month of policy start_date. Note that we use to truncate the date to the month, so we can group by month. The condition is used to exclude policies that have ended before the month we're calculating for.

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

SQL Question 5: How does a left join differ from a right join?

Both left and right joins in SQL allow you to combine data from different tables based on a shared key or set of keys. For a concrete example of the difference between these two join types, say you had sales data exported from State Farm's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .

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

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

SQL Question 6: Filter Customers with Specific Policy Types

State Farm, as an insurance provider, maintains a customer records database that holds detailed information about its customers and their insurance policies. Often, the company needs to identify customers based on their insurance policies, such as those who have both auto and home insurance or those who have neither.

Your task is to write a PostgreSQL query that will filter the customer records to find customers:

a) who have both auto and home insurance, b) who have either auto or home insurance but not both, c) who do not have either auto or home insurance.

Please refer to the following tables:

Example Input:

Example Input:

Example Output for condition a):

Example Output for condition b):

Example Output for condition c):

Answer:

a)

This query first selects all customers and then filters for those having both auto and home insurance, using subqueries in the WHERE clause.

b)

This query uses the XOR (exclusive OR) operator to find customers who have either auto or home insurance but not both.

c)

This query uses the NOT EXISTS operator to exclude customers who have either auto or home insurance.

SQL Question 7: Why might you denormalize a database?

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

For example, in a database that stores State Farm sales analytics data, you might have separate tables for , , and , with foreign key constraints linking the tables together. This helps to ensure the integrity of the data and reduces redundancy, but it can also make queries that involve multiple tables more complex and slower to execute.

By de-normalizing the database, you can combine some of the data from separate tables into a single table, which can reduce the number of joins that are required to retrieve the data you need. This can speed up queries and improve the performance of your database.

However, it's important to carefully consider the trade-offs of de-normalization before making any changes to your database. De-normalization can make it more difficult to maintain the integrity and reliability of your data, and can also increase the risk of data redundancy. It's generally best to use de-normalization as a performance optimization technique only when necessary, and to carefully evaluate the benefits and drawbacks in the context of your specific database and workload.

SQL Question 8: Determine the Click-Through Rates

As an analyst at State Farm, one of your responsibilities is to track and evaluate the effectiveness of the company's digital advertisements. The typical measure for this is the click-through rate (CTR). State Farm shows digital ads to potential customers, and each time these ads are clicked on, it brings them to the quote page of the State Farm website. From here, the potential customer can either choose to follow through and request a quote or exit the page.

Can you write a SQL query to calculate the click-through rate, from ad view to quote request, for the past month? For each advertising channel (for example, Facebook, Google, etc.), provide the click-through rates.

Example Input:

Example Input:

Answer:

Here's your SQL solution with PostgreSQL:

The above query calculates the total distinct user views and quote requests per channel for the last month. Then it calculates the click-through rate as the proportion of quote requests to ad views.

To solve a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's interactive SQL code editor:

SQL Question 9: Calculate Average Premium for Each Insurance Type

Given a database table, , containing information about each insurance policy that State Farm has sold, such as , , , (like auto, home, life, etc.), and cost. Your task is to write an SQL query that calculates the average annual premium for each insurance type.

Example Input:

Example Output:

Answer:

This PostgreSQL query uses the GROUP BY clause to group all policies by their type. Then, for each group, it calculates the average () annual premium. The output is a list of insurance types alongside their corresponding average annual premium.

SQL Question 10: What is a cross-join?

A cross-join, also known as a cartesian join, is a JOIN that produces the cross-product of two tables. In a cross-join, each row from the first table is matched with every row from the second table, resulting in a new table with a row for each possible combination of rows from the two input tables.

Let's say you were building a Machine Learning model that attempts to score the probability of a customer purchasing a State Farm product. Before working in Pandas and Tensorflow, you might want to do some Exploratory Data Analysis (EDA) in SQL, and generate all pairs of customers and State Farm products.

Here's a cross-join query you could run:

Cross-joins are useful for generating all possible combinations, but they can also create huge tables if you're not careful. For instance, if you had 10,000 potential customers and State Farm had 500 different product SKUs, the resulting cross-join would have 5 million rows!

SQL Question 11: Query to Find Specific Pattern in Customer Records

State Farm has a database that contains information about each customer, including the customer's name, email, and address. The marketing team wants to identify customers in California to target for a new marketing campaign. They want to list all the customers whose address matches the pattern 'CA' at the end, denoting they live in California.

Can you craft an SQL query that will filter and output customer records where the 'address' field ends with 'CA'?

Example Input:

Example Output:

Answer:

This PostgreSQL query uses the LIKE keyword to filter records that match a specific pattern. The symbol '%' is a wildcard in SQL that matches any sequence of characters. By placing it before 'CA', we specify that we're looking for any records where the 'address' field ends with 'CA'.

How To Prepare for the State Farm SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the State Farm SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above State Farm 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, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an interactive SQL code editor so you can right in the browser run your query and have it checked.

To prep for the State Farm SQL interview you can also be a great idea to practice SQL questions from other insurance companies like:

• Liberty Mutual SQL questions
• MetLife SQL questions
• AllState SQL questions
• AIG SQL questions

Learn how State Farm is leveraging innovation to create a better customer experience!

However, if your SQL foundations are weak, forget about jumping right into solving questions – refresh your SQL knowledge with this SQL interview tutorial.

This tutorial covers topics including how window functions work and handling dates – both of which show up frequently in SQL job interviews at State Farm.

State Farm Insurance Data Science Interview Tips

What Do State Farm Data Science Interviews Cover?

Beyond writing SQL queries, the other topics to practice for the State Farm Data Science Interview include:

• AB Testing Questions
• Python or R Coding Questions
• Open-Ended Data Case Studies
• ML Interview Questions
• Behavioral Interview Questions

How To Prepare for State Farm Data Science Interviews?

I believe the optimal way to prep for State Farm Data Science interviews is to read the book Ace the Data Science Interview.

It solves 201 data interview questions sourced from FAANG, tech startups, and Wall Street. The book's also got a refresher on Stats, ML, & Data Case Studies. And finally it's vouched for by the data community, which is why it's earned 1000+ reviews on Amazon and a 4.5-star rating.

Learn about how State Farm and other Insurance Companies use Data Science through 7 Real World Examples.

While the book is more technical, it's also important to prepare for the State Farm behavioral interview. Start by reading the company's culture and values.