# 8 First American SQL Interview Questions (Updated 2024)

Updated on

June 30, 2024

First American employees write SQL queries often for extracting and analyzing data from real estate databases, and for optimizing data management systems. That's the reason behind why First American LOVES to ask SQL query questions during interviews for Data Science, Analytics, and & Data Engineering jobs.

Thus, to help you study for the First American SQL interview, we've collected 8 First American Financial SQL interview questions can you solve them?

## 8 First American Financial SQL Interview Questions

### SQL Question 1: Identify the "Whale" Customers for First American.

First American is a title insurance and settlement services company. In this case, a "whale" customer could be one who orders a high volume of these services, possibly indicating they are either large-scale property developers or involved in many property transactions.

Let's consider the company's transactions database for this analysis and identify the customers who made the most orders in the last quarter (3 months). "Most orders" could be defined in several ways, such as most in number or most in terms of total cost - for this analysis, let's use the total cost of the services ordered by the customer.

We will identify the top 10 customers by this measure.

##### Example Input:
order_idcustomer_idorder_dateservice_idtotal_cost
41821304507/10/202220012$450 79749540007/11/202220789$200
52989304507/14/202220012$550 63424180907/15/202220789$350
45170540007/18/202220012$250 20903108307/20/202220012$500
35091108307/30/202220789$600 ##### Example Output: customer_idtotal_cost 3045$1000
5400$450 1083$1100

This select statement starts by selecting from the "orders" table. The WHERE clause after FROM filters the orders by order_date so that only orders from the last quarter are considered. The SELECT clause then groups the remaining orders by customer_id, while also calculating the total cost of all orders for each customer. Finally, the ORDER BY and LIMIT clauses sort the results in descending order by total_cost and limit the output to the top 10 customers.

To work on another SQL customer analytics question where you can solve it interactively and have your SQL solution automatically checked, try this Walmart Labs SQL Interview Question:

### SQL Question 2: Second Highest Salary

Suppose there was a table of First American employee salary data. Write a SQL query to find the 2nd highest salary at the company.

#### First American Example Input:

employee_idsalary
12500
2800
31000
41200

#### Example Output:

second_highest_salary
1200

You can solve this interview question interactively on DataLemur:

You can find a detailed solution with hints here: 2nd Highest Salary.

Read about First American's Data solutions team and how the company uses sql in their day-to-day practices.

### SQL Question 3: How does the RANK() window function differ from DENSE_RANK()?

In SQL, both and are used to rank rows within a result set. The key difference between the two functions is how deal with two or more rows having the same value in the ranked column (aka how the break ties).

RANK(): When there's a tie, leaves a gap in the ranking. For example, if three rows are tied for 2nd place, the RANK() function will assign a rank of 2 to the first of these rows, a rank of 3 to the second row, and a rank of 4 to the third row.

DENSE_RANK(): For ties, does not leave a gap in the ranking. Instead, it assigns the same rank to all tied rows, and then makes the next row 1 bigger. Confusing, I know, but here's an example to make it more clear: if three rows are tied for 3rd place, the function will assign a rank of 3 to all three rows, and then assign a rank of 4 to the next row.

SQL Question 4: Calculate Monthly Average Interest Rates and Total Loan Amounts {#Question-4}

First American Financial Corporation is a leading provider of title insurance and settlement services to the real estate and mortgage industries. As an analyst, one common task might be to write a SQL query to calculate the average monthly interest rate and the total loan amount for each client.

Assume there is a table 'loans' with 'loan_id', 'client_id', 'interest_rate', 'loan_amount' and 'loan_date' properties. Here's an example of the 'loans' table:

##### Example Input:
loan_idclient_idinterest_rateloan_amountloan_date
100113.755000002022-01-16
100213.256000002022-02-15
100323.504000002022-02-16
100423.254500002022-03-15
100533.755500002022-03-16

The goal is to write a query that produces the following result:

##### Example Output:
monthclient_idaverage_interest_ratetotal_loan_amount
0113.75500000
0213.25600000
0223.50400000
0323.25450000
0333.75550000

The SQL query to derive the above output would look like this,

This PostgreSQL query first partitions the 'loans' table by 'client_id' and month (extracted from 'loan_date'). For each partition, it computes the average 'interest_rate' and the total 'loan_amount'. It then orders the final result by 'month' and 'client_id'. The TO_CHAR function is used to get the month part of the 'loan_date' and the AVG and SUM functions operate on the respective partitions.

To solve a similar window function question on DataLemur's free online SQL code editor, try this Google SQL Interview Question:

### SQL Question 5: What's a database view, and what's it used for?

A database view is a virtual table that is created based on the results of a SELECT statement, and provides you a customized, read-only version of your data that you can query just like a regular table.

You'd want to use a view for a few reasons:

• views allow you to create a simpler versions of your data based on whose running the query (such as hiding un-important columns/rows from business analysts if they're just random noisy artifricats of your Data Infrastructure pipelines)
• views can help you comply with information security requirements by hiding sensitive data from certain users (important for regulated industries like govermnet and healthcare!)
• views often improve performance for complicated queries by pre-computing the results and saving them in a view (which is often faster than re-executing the original query)... just be careful since static views don't update if the underlying data changes!

### SQL Question 6: Determine the Click-Through Rate for First American's Marketing Ads

First American is a company that heavily uses digital marketing. Their Marketing team wants to evaluate the efficiency of these campaigns by analyzing the Click-Through Rate (CTR) during the last quarter. The CTR is calculated by taking the number of clicks ads receive divided by the number of total impressions.

You have given two tables – Impressions and Clicks. The Impressions table records all the ads which were displayed, and the Clicks table captures all users who clicked on those ads.

##### Example Input:
512100106/23/2022 00:00:001287
534100307/12/2022 00:00:002356
540100206/18/2022 00:00:003602
586100107/16/2022 00:00:001982
605100307/01/2022 00:00:009811
##### Example Input:
791100106/23/2022 00:00:001287
826100107/16/2022 00:00:001982
839100206/18/2022 00:00:003602
842100307/01/2022 00:00:009811

Write a SQL query that computes the total number of impressions, total number of clicks and the Click-Through Rate (CTR) per advertisement in the last quarter.

This SQL query is used to obtain the total number of impressions and clicks for each ad in the last quarter, and then calculate the CTR by dividing the number of clicks by the number of impressions. We perform a LEFT JOIN on Ad_id and User_id because it ensures that we consider all impressions, even if they didn't translate into a click. We use COUNT DISTINCT because we are interested in unique clicks and impressions. The CTR value is expressed as a decimal fraction.

To solve a related problem on DataLemur's free online SQL code editor, try this SQL interview question asked by Facebook:

### SQL Question 7: What sets the 'BETWEEN' and 'IN' operators apart?

While both the and operators are used to filter data based on some criteria, selects for values within a given range, whereas for it checks if the value is in a given list of values.

For example, say you had a table called , which had the salary of the employee, along with the country in which they reside.

To find all employees who made between $80k and$120k, you could use the operator:

To find all employees that reside in the US or Canada, you could use the operator:

### SQL Question 8: Calculate the Sales Volume along with Discounted Amount

First American Corporation wants to estimate its monthly sales volume as well as the total discount amount given to the customers. They are interested in observing the effect of discounts on the sales volume. The sale record is stored in the table, which includes details like the product sold, its quantity and the price. The table also includes details of any discounts offered on the product. Write a SQL query to calculate the total sale volume and the total discounted amount offered in each month. You are required to use various arithmetic operators such as '+', '-', '*' and '/' for performing operations like subtraction and division for these calculations. Use the ROUND() function to round off the discounted amount.

Here's an example of table:

##### Example Input:
sale_idsale_dateproduct_idqtyprice_per_unitdiscount_percentage
1012023-01-15100110300.10
1022023-01-20100215200.15
1032023-02-10100120300.10
1042023-02-1510038400.05
1052023-03-0510027200.20

Expected output:

sale_monthtotal_sale_volumetotal_discounted_amount
1800105
288060
314028

PostgreSQL query is given below:

The SQL query first groups the table by , which is a column generated by extracting month from . Once the data is grouped based on the month, the function calculates the total sale volume as well as the total discounted amount in each month. The total sale volume is calculated by multiplying with for each product. The total discounted amount is calculated by multiplying the total sale amount of each product with the offered on it. The function is used to round off the total discounted amount to two decimal places. Finally, the clause is used to sort the output based on .

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for requiring calculation of sales data or this Amazon Highest-Grossing Items Question which is similar for involving sales and product details.

### Preparing For The First American SQL Interview

The best way to prepare for a First American SQL interview is to practice, practice, practice. Beyond just solving the earlier First American SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Netflix, Google, and Amazon.

Each exercise has hints to guide you, detailed solutions and crucially, there's an interactive coding environment so you can instantly run your SQL query and have it executed.

To prep for the First American SQL interview you can also be helpful to practice SQL problems from other mortgage & insurance companies like:

In case your SQL skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

This tutorial covers things like UNION vs. joins and ordering data – both of which pop up frequently in First American SQL assessments.

### First American Financial Data Science Interview Tips

#### What Do First American Data Science Interviews Cover?

In addition to SQL interview questions, the other topics tested in the First American Data Science Interview include:

• Stats Interview Questions
• Coding Questions in Python or R
• Product Analytics Questions
• ML Modelling Questions
• Resume-Based Behavioral Questions

#### How To Prepare for First American Data Science Interviews?

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