9 Wynn Resorts SQL Interview Questions (Updated 2024)
Data Scientists, Analysts, and Data Engineers at Wynn Resorts are writing SQL queries to analyze customer behavior, allowing them to tailor promotions that resonate with guests and enhance their overall experience. They also use SQL to optimize hotel booking systems, ensuring that operations run smoothly and and boosting revenue in the process, which is why Wynn Resorts asks SQL coding interview questions during job interviews.
To help you ace the Wynn Resorts SQL interview, we've curated 9 Wynn Resorts SQL interview questions in this article.
9 Wynn Resorts SQL Interview Questions
SQL Question 1: Identify Top Spending Guests at Wynn Resorts
Wynn Resorts wants to identify its VIP customers, i.e., guests who have spent the most at their resorts in the past year. Assume that the company tracks every transaction a guest makes, from room charges to restaurant bills, spa services, and in-resort purchases.
Assuming we have the following two tables:
Example Input:
| guest_id | first_name | last_name |
|---|---|---|
| 101 | John | Doe |
| 102 | Jane | Smith |
| 103 | Billy | Barker |
| 104 | Sally | Fields |
| 105 | Robert | Nelsen |
Example Input:
| transaction_id | guest_id | transaction_date | amount |
|---|---|---|---|
| 9001 | 101 | 05/23/2021 | 250 |
| 9002 | 102 | 05/23/2021 | 350 |
| 9003 | 105 | 05/23/2021 | 450 |
| 9004 | 101 | 05/27/2021 | 300 |
| 9005 | 104 | 06/03/2021 | 200 |
Create a SQL query to identify top 5 guests who spent the most in the past year, along with their total spend.
Answer:
With this query, we first join the and tables on . We then filter for transactions made in the last year. The clause groups the results by guests, and the function calculates the total spend per guest. Finally, we total spend in descending order and the result to 5, to get the top 5 spending guests.
To solve a related customer analytics question on DataLemur's free online SQL code editor, try this recently asked Microsoft SQL interview question:
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SQL Question 2: Well Paid Employees
Given a table of Wynn Resorts employee salary data, write a SQL query to find employees who earn more than their own manager.
Wynn Resorts Example Input:
| employee_id | name | salary | department_id | manager_id |
|---|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 | |
| 2 | Daniel Rodriguez | 2230 | 1 | 10 |
| 3 | Olivia Smith | 8000 | 1 | 8 |
| 4 | Noah Johnson | 6800 | 2 | 8 |
| 5 | Sophia Martinez | 1750 | 1 | 10 |
| 8 | William Davis | 7000 | 2 | NULL |
| 10 | James Anderson | 4000 | 1 | NULL |
Example Output:
| employee_id | employee_name |
|---|---|
| 3 | Olivia Smith |
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 interview question directly within the browser on DataLemur:
Answer:
First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.
If the code above is confusing, you can find a step-by-step solution here: Employees Earning More Than Managers.
SQL Question 3: What is database normalization?
Database normalization is the process of breaking down a table into smaller and more specific tables and defining relationships between them via foreign keys. This minimizes redundancy, and creates a database that's more flexible, scalable, and easier to maintain. It also helps to ensure the integrity of the data by minimizing the risk of data inconsistencies and anomalies.
SQL Question 4: Analyzing Guest Bookings
As a data scientist in Wynn Resorts, you have been given access to the Guest Booking dataset. You are tasked to provide a list of all guests () with the total number of room bookings () they have made over the course of their membership. Also, the query should progressively sum the total bookings for each across their , from earliest to most recent. This is often referred to as a running total or cumulative sum.
The data table looks like the following:
Example Input:
| booking_id | guest_id | booking_date | room_id |
|---|---|---|---|
| 1001 | 150 | 01/15/2022 | 5874 |
| 2002 | 325 | 01/20/2022 | 6952 |
| 3003 | 150 | 01/28/2022 | 5874 |
| 4004 | 192 | 02/05/2022 | 8704 |
| 5005 | 150 | 02/25/2022 | 6952 |
Answer:
In this query, we first create a CTE (Common Table Expression) where we partition the data by and calculate the running total of room bookings. We use the clause to specify the window over which the running total is calculated - from the first booking of guest to the current row.
The final select statement then orders the result by and , to allow easy inspection of the running sum of bookings for each guest.
Pro Tip: Window functions are a popular SQL interview topic, so practice every window function problem on DataLemur
SQL Question 5: What sets relational and NoSQL databases apart?
While knowing this answer is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Wynn Resorts should be at least aware of SQL vs. NoSQL databases.
Relational databases and non-relational (NoSQL) databases have some key differences, particularly in terms of how data is stored. Whereas relational databases have tables, made up of rows and columns, NoSQL databases use various data models like:
- Wide-Column Stores – this database uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row within the same table
- Key-Value Stores – instead of rows and columns, you have keys, where each key is associated with only one value in a collection (similar to a Python dictionary data structure!)
- Graph Stores – instead of rows of data, you have nodes, and then can also have edges between entities (much like a Graph Data Structure for those who've taken a Computer Science data structures & algorithms class)
This added flexibility makes NoSQL databases well-suited for handling non-tabular data or data with a constantly changing format. However, this flexibility comes at the cost of ACID compliance, which is a set of properties (atomic, consistent, isolated, and durable) that ensure the reliability and integrity of data in a database. While most relational databases are ACID-compliant, NoSQL databases may not provide the same level of guarantees.
SQL Question 6: Calculate the Average Revenue from Different Resort Services
Wynn Resorts provides multiple services to their guests such as rooms, food and beverages, and entertainment. You are tasked with writing a SQL query to find the average revenue generated by each service in the last year.
Here's the formatting for the table .
Example Input:
| transaction_id | service_type | transaction_date | revenue |
|---|---|---|---|
| 1234 | Room | 2021-09-01 | 200.00 |
| 2345 | Food and Beverage | 2021-10-02 | 75.00 |
| 3456 | Entertainment | 2021-11-15 | 150.00 |
| 4567 | Room | 2021-10-10 | 225.00 |
| 5678 | Food and Beverage | 2021-09-20 | 100.00 |
Example Output:
| service_type | avg_revenue |
|---|---|
| Room | 212.50 |
| Food and Beverage | 87.50 |
| Entertainment | 150.00 |
Answer:
The PostgreSQL query for this question would be:
This query selects the and the average from the table. The clause filters the query to only include transactions that took place in 2021. The statement is used to group the results by . The average revenue for each service type is then calculated using the aggregate function.
SQL Question 7: What does do?
The function can be used to replace NULL values with a specified value. For instance, if you are a Data Analyst at a company and are working on a customer analytics project to identify the most engaged customers, you may have access to the following data in the table:
| customer_id | email_engagement | sms_engagement |
|---|---|---|
| 101 | moderately_active | not_opted_in |
| 201 | un-subscribed | NULL |
| 301 | NULL | not_opted_in |
| 401 | not_active | very_active |
| 501 | very_active | very_active |
| 601 | NULL | NULL |
Before you could proceed with your analysis, you would need to remove the NULLs and replace them with the default value for email engagement (), and the default SMS engagement level ().
To do this, you'd run the following query:
This would get you the following output:
| customer_id | email_engagement | sms_engagement |
|---|---|---|
| 101 | moderately_active | not_opted_in |
| 102 | un-subscribed | not_opted_in |
| 103 | not_active | not_opted_in |
| 104 | not_active | very_active |
| 105 | very_active | very_active |
| 106 | not_active | not_opted_in |
SQL Question 8: Retrieve Guests with a Particular Surname
At Wynn Resorts, the database stores information about the guests. The staff has a task to retrieve a list of guests who have a surname that starts with "M". For this task, they have to filter down the guests from the table where their starts with "M".
Example Input:
| guest_id | first_name | last_name | reservation_date |
|---|---|---|---|
| 9925 | John | Smith | 06/01/2022 00:00:00 |
| 11152 | Anna | Martinez | 06/06/2022 00:00:00 |
| 76321 | Pedro | Moreno | 06/18/2022 00:00:00 |
| 86592 | Alice | Brown | 07/26/2022 00:00:00 |
| 72358 | Sam | Michael | 07/05/2022 00:00:00 |
Expected Output:
| guest_id | first_name | last_name |
|---|---|---|
| 11152 | Anna | Martinez |
| 76321 | Pedro | Moreno |
| 72358 | Sam | Michael |
Answer:
This SQL query uses the LIKE operator to perform a pattern match. It filters out guest records from table where starts with 'M'. The '%' wildcard character is used after 'M' to match any sequence of characters following it. Thus, it retrieves all guests whose last names start with 'M'.
SQL Question 9: Analysis of customer and reservation data for Wynn Resorts
As a Data Analyst at Wynn Resorts, you are asked to write a SQL query to retrieve a list of customers who have made a reservation in the last 30 days (from today) and their total spend. The necessary data is located in two different tables: and .
Join these two tables properly to get the required information. The field is common in both tables.
Example Input:
| customer_id | first_name | last_name | |
|---|---|---|---|
| 123 | John | Smith | johnsmith@mail.com |
| 265 | Amanda | White | amandawhite@mail.com |
| 362 | Peter | Brown | peterbrown@mail.com |
Example Input:
| reservation_id | customer_id | reservation_date | total_spent |
|---|---|---|---|
| 6171 | 123 | 06/16/2022 | 500 |
| 7802 | 265 | 07/10/2022 | 400 |
| 5293 | 362 | 07/15/2022 | 300 |
Assume today's date is 07/22/2022.
Answer:
The above PostgreSQL query runs through the and tables. It uses the clause to combine rows from these two tables, based on the they have in common. The clause is used to filter out reservations that are older than 30 days. The function is used to calculate the total expenditure of each customer who has made a reservation in the last 30 days. The statement is used to group the results by .
Since join questions come up routinely during SQL interviews, practice an interactive Spotify JOIN SQL question:
Preparing For The Wynn Resorts SQL Interview
The key to acing a Wynn Resorts SQL interview is to practice, practice, and then practice some more! In addition to solving the above Wynn Resorts SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.
Each DataLemur SQL question has multiple hints, detailed solutions and most importantly, there is an online SQL code editor so you can right in the browser run your query and have it checked.
To prep for the Wynn Resorts SQL interview it is also wise to practice interview questions from other hospitality and restaurant companies like:
In case your SQL foundations are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this free SQL for Data Analytics course.
This tutorial covers topics including INTERCEPT/EXCEPT and filtering on multiple conditions using AND/OR/NOT – both of which show up frequently in Wynn Resorts SQL assessments.
Wynn Resorts Data Science Interview Tips
What Do Wynn Resorts Data Science Interviews Cover?
Beyond writing SQL queries, the other types of questions tested in the Wynn Resorts Data Science Interview are:
- Probability & Statistics Questions
- Python or R Coding Questions
- Product-Sense and Business Case Questions
- Machine Learning Questions
- Behavioral Based Interview Questions
How To Prepare for Wynn Resorts Data Science Interviews?
I believe the optimal way to prep for Wynn Resorts Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
It solves 201 data interview questions sourced from tech companies like Netflix, Google, & Airbnb. The book's also got a crash course covering SQL, Product-Sense & ML. And finally it's vouched for by the data community, which is why it's got over 1000+ 5-star reviews on Amazon.
While the book is more technical, it's also key to prepare for the Wynn Resorts behavioral interview. A good place to start is by reading the company's values and mission.