8 Boyd Gaming SQL Interview Questions (Updated 2024)

At Boyd Gaming, SQL is used for analyzing customer gaming behaviors, allowing them to create marketing strategies that align with their players' preferences. They also use SQL to manage large transactional databases, ensuring that operations run smoothly and efficiently across their gaming properties, this is why Boyd Gaming includes SQL questions in their interviews for Data Science and Data Engineering jobs.

So, to help you prep, we've collected 8 Boyd Gaming SQL interview questions – can you answer each one?

8 Boyd Gaming SQL Interview Questions

SQL Question 1: Calculate the Monthly Average Revenue By Game

As a data analyst at Boyd Gaming, your manager wants you to analyze the monthly average revenue generated by each game. The company wants to know if some games are performing better than others.

You are given a table called revenues with columns:

1. transaction_id - the unique id of each transaction
2. game_id - the unique id of each game
3. player_id - the unique id of each player
4. transaction_date - the date when transaction occurred
5. amount - the amount of money spent by player

Write a SQL query that calculates the monthly average revenue per game.

revenues Example Input:

Example Output:

Answer:

SELECT 
    DATE_TRUNC('month', transaction_date) AS monthly_period, 
    game_id, 
    AVG(amount) AS avg_revenue 
FROM 
    revenues 
GROUP BY  
    monthly_period, 
    game_id 
ORDER BY 
    monthly_period, 
    game_id;

This AS statement creates an alias for DATE_TRUNC('month', transaction_date) as monthly_period. We group by monthly_period and game_id to calculate the average revenue for each game each month. The ORDER BY statement sorts the result by monthly_period and then by game_id for easier readability.

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

Stay updated with Boyd Gaming's press releases and see how they are reshaping the gaming and hospitality landscape with new initiatives and community-focused events! This information can help you grasp the strategies that successful companies use to connect with their audiences.

SQL Question 2: Well Paid Employees

Given a table of Boyd Gaming employee salary data, write a SQL query to find employees who make more than their own boss.

Boyd Gaming employees Example Input:

Example Output:

This is the output because Olivia Smith earns $8,000, surpassing her manager, William Davis who earns 7,800.

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

Answer:

First, we perform a SELF-JOIN where we treat the first employee table (mgr) as the managers' table and the second employee table (emp) as the employees' table. Then we use a WHERE clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

SELECT
  emp.employee_id AS employee_id,
  emp.name AS employee_name
FROM employee AS mgr
INNER JOIN employee AS emp
  ON mgr.employee_id = emp.manager_id
WHERE emp.salary > mgr.salary;

If the solution above is tough, you can find a detailed solution here: Highly-Paid Employees.

SQL Question 3: What do the SQL commands EXCEPT / MINUS do?

The MINUS/EXCEPT operator is used to return all rows from the first SELECT statement that are not returned by the second SELECT statement.

Note that EXCEPT is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at Boyd Gaming should be lenient!).

Here's a PostgreSQL example of using EXCEPT to find all of Boyd Gaming's Facebook video ads with more than 10k views that aren't also being run on YouTube:

SELECT ad_creative_id
FROM boyd_gaming_facebook_ads
WHERE views > 10000 AND type=video

EXCEPT

SELECT ad_creative_id
FROM boyd_gaming_youtube_ads

If you want to retain duplicates, you can use the EXCEPT ALL operator instead of EXCEPT. The EXCEPT ALL operator will return all rows, including duplicates.

SQL Question 4: Average Monthly Revenue of Each Boyd Gaming Casino

We want to understand the performance of each casino in our portfolio. Write an SQL query to find out the average monthly revenue of each Boyd Gaming casino.

casinos Example Input:

revenue Example Input:

Example Output:

Answer:

SELECT c.casino_name, AVG(r.revenue) AS average_monthly_revenue
FROM casinos c
JOIN revenue r ON c.casino_id = r.casino_id
GROUP BY c.casino_name;

This query joins the casinos and revenue tables on casino_id. It then groups the result by casino_name and calculates the average revenue, providing the average monthly revenue of each casino.

SQL Question 5: What does it mean to use a UNIQUE constraint in a database?

The UNIQUE constraint is used to ensure the uniqueness of the data in a column or set of columns in a table. It prevents the insertion of duplicate values in the specified column or columns and helps to ensure the integrity and reliability of the data in the database.

For example, say you were on the Marketing Analytics team at Boyd Gaming and were doing some automated keyword research:

Your keyword database might store SEO data like this:

CREATE TABLE keywords (
    keyword_id INTEGER PRIMARY KEY,
    keyword VARCHAR(255) NOT NULL UNIQUE,
    search_volume INTEGER NOT NULL,
    competition FLOAT NOT NULL
);

In this example, the UNIQUE constraint is applied to the keyword field to ensure that each keyword is unique. This helps to ensure the integrity of the data in the database and prevents errors that could occur if two rows had the same keyword.

SQL Question 6: Find Customers with Specific Gambling Activity

As a part of the business analytics team at Boyd Gaming, your task is to analyze the customer activity patterns to target them with personalized promotions. Write an SQL query to find all the customers whose gamble name start with 'Black' from the customer_records table.

customer_records Example Input:

Example Output:

Answer:

SELECT customer_id, customer_name, gamble_game
FROM customer_records
WHERE gamble_game LIKE 'Black%';

This SQL query filters the data in the customer_records table to only include customers who played games that start with 'Black'. The SQL LIKE operator is used here with the wildcard character % to find matches in the gamble_game column where the game name starts with 'Black'. It returns the customer_id, customer_name, and the gamble_game they participated in from the customer_records table.

SQL Question 7: What do primary keys do?

A primary key is a column or group of columns that uniquely identifies a row in a table. For example, say you had a database of Boyd Gaming marketing campaigns data:

CREATE TABLE MarketingCampaigns (
    CampaignID INTEGER PRIMARY KEY,
    CampaignName VARCHAR(255),
    StartDate DATE,
    EndDate DATE,
    Budget DECIMAL(8,2)
);

In this Boyd Gaming example, the CampaignID column is the primary key of the MarketingCampaigns table. The PRIMARY KEY constraint ensures that no two rows have the same CampaignID. This helps to maintain the integrity of the data in the table by preventing duplicate rows.

SQL Question 8: Analyze the Effect of Casino Financing on Customer Visits

Boyd Gaming, a successful gaming and hospitality company, maintains two databases:

1. customers which includes customer details and their household income, and
2. finance that stores the financing options provided at different casinos.

Write a SQL query to join these tables and calculate the average household income of customers from each financing category.

Please be sure to consider only customers who have visited a casino at least twice.

customers Example Input:

finance Example Input:

Answer:

SELECT 
  f.financing_category,
  AVG(c.household_income) AS avg_household_income
FROM 
  customers AS c
JOIN 
  finance AS f  
ON 
  c.customer_id = f.customer_id
WHERE 
  c.casino_visits >= 2
GROUP BY 
  f.financing_category;

This query starts by joining the customers table to the finance table on the customer_id column. It then filters to only include customers who have visited a casino at least twice (as indicated by c.casino_visits >= 2).

The GROUP BY clause groups the remaining rows by the financing category they belong to. The AVG(c.household_income) function then calculates the average household income for each of these categories. The result is a list of financing categories along with the average household income of customers who belong to them.

Since join questions come up frequently during SQL interviews, take a stab at this Spotify JOIN SQL question:

How To Prepare for the Boyd Gaming SQL Interview

The best way to prepare for a Boyd Gaming SQL interview is to practice, practice, practice. In addition to solving the earlier Boyd Gaming SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like FAANG tech companies and tech startups.

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

To prep for the Boyd Gaming SQL interview you can also be a great idea to practice interview questions from other hospitality and restaurant companies like:

• Wynn Resorts SQL questions
• Darden Restaurants SQL questions
• Marriott SQL questions
• Cracker Barrel SQL questions

However, if your SQL coding skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.

This tutorial covers SQL concepts such as sorting data with ORDER BY and CASE/WHEN/ELSE statements – both of which show up routinely during Boyd Gaming SQL assessments.

Boyd Gaming Data Science Interview Tips

What Do Boyd Gaming Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions tested in the Boyd Gaming Data Science Interview include:

• Probability & Stats Questions
• Python Pandas or R Coding Questions
• Open-Ended Data Case Studies
• ML Modelling Questions
• Behavioral & Resume-Based Questions

How To Prepare for Boyd Gaming Data Science Interviews?

I think the best way to study for Boyd Gaming Data Science interviews is to read the book Ace the Data Science Interview.

It covers 201 interview questions taken from Google, Microsoft & tech startups. The book's also got a refresher on Stats, ML, & Data Case Studies. And finally it's helped thousands of people land their dream job in data, which is why it's got over 1000+ 5-star reviews on Amazon.

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