10 Hilton SQL Interview Questions (Updated 2024)
At Hilton Worldwide Holdings, they rely on SQL to analyze customer booking patterns to create personalized marketing campaigns that match guests' preferences. It is also used to manage hotel inventory effectively, ensuring that room availability and pricing are optimized to meet demand, this is the reason why Hilton evaluates jobseekers with SQL questions during interviews for Data Science and Data Engineering positions.
To help you prepare for the Hilton SQL interview, we've curated 10 Hilton Worldwide Holdings SQL interview questions – can you solve them?
10 Hilton Worldwide Holdings SQL Interview Questions
SQL Question 1: Find the average review score for Hilton Hotels per city, per month, ranking cities with the highest average in descending order.
As a Data Analyst for Hilton, you are tasked with analyzing the company's guest reviews. Write a SQL query to calculate the average review score () for Hilton Hotels per city, per month, ranking cities with the highest average first. For each city, also calculate the difference in the average review score from the previous month.
Let's consider the following tables:
Example Input:
| review_id | hotel_id | submit_date | stars |
|---|---|---|---|
| 6171 | H001 | 2022-06-08 | 4 |
| 7802 | H007 | 2022-06-10 | 4 |
| 5293 | H001 | 2022-05-18 | 3 |
| 6352 | H007 | 2022-07-26 | 3 |
| 4517 | H003 | 2022-05-05 | 2 |
Example Input:
| hotel_id | city |
|---|---|
| H001 | New York |
| H002 | Los Angeles |
| H003 | Chicago |
| H004 | San Francisco |
| H005 | Boston |
| H006 | Washington D.C. |
| H007 | Austin |
Answer:
In the query, we first join the reviews and hotels tables to link the hotel id to its city. We then create a window frame partitioned by month and city, calculating the average review score for each month and city, and the difference from the average score of the previous month. Finally, we select the desired columns and order them by the average review score in descending order and month in ascending order.
To practice a similar window function question on DataLemur's free interactive SQL code editor, solve this Google SQL Interview Question:
Discover the latest stories and updates from Hilton that showcase their commitment to hospitality and guest experience! By following Hilton's news, you can learn more about how they are setting trends in the hotel industry.
SQL Question 2: Employees Earning More Than Their Boss
Given a table of Hilton employee salary data, write a SQL query to find all employees who earn more money than their own boss.
Hilton 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.
Try this interview question and run your code right in DataLemur's online SQL environment:
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 tough, you can find a step-by-step solution here: Well Paid Employees.
SQL Question 3: How do the SQL commands and differ?
For all practical purposes, and do NOT produce the same results.
While both are similar in that they combine two tables, you can think of joins as increasing the width of the resulting table (you'll have more columns in the result set for a left/inner/right join), whereas a union is used to combine rows which increases the height of the result set but keeps the column count the same.
If your familiar with set operations, you can think of a as set addition, whereas a is set multiplication.
SQL Question 4: Hotel Booking Analysis
As a data analyst at Hilton, you are tasked with analyzing booking trends across various hotel properties. The company is interested in understanding the booking trends for different types of rooms, based on customer location and time of booking. Given the tables and , design a SQL query to find out the number of bookings per room type for each month, for customers from USA and UK.
Assume we have the following two tables:
Example Input:
| booking_id | customer_id | booking_date | property_id | room_type |
|---|---|---|---|---|
| 1 | 101 | 2022-08-01 | 1 | Deluxe |
| 2 | 102 | 2022-08-15 | 1 | Standard |
| 3 | 103 | 2022-09-10 | 2 | Deluxe |
| 4 | 104 | 2022-09-15 | 2 | Standard |
| 5 | 105 | 2022-10-01 | 3 | Suite |
Example Input:
| customer_id | customer_name | country |
|---|---|---|
| 101 | John Doe | USA |
| 102 | Alex Smith | UK |
| 103 | Lucy Johnson | USA |
| 104 | Emma Brown | UK |
| 105 | James Wilson | UK |
Answer:
Here is the PostgreSQL query to solve this:
This query first joins the bookings and customer tables on the column. It then filters the records to only include customers from the USA and UK. Then, it groups the results by the booking month, room type, and country. It calculates the total number of bookings for each group and finally orders the results by the booking month and number of bookings in descending order.
SQL Question 5: How is the constraint used in a database?
A is a column or set of columns in a table that references the primary key of another table. It is used to link the two tables together, and to ensure that the data in the foreign key column is valid.
The constraint helps to ensure the integrity of the data in the database by preventing the insertion of rows in the foreign key table that do not have corresponding entries in the primary key table. It also helps to enforce the relationship between the two tables and can be used to ensure that data is not deleted from the primary key table if there are still references to it in the foreign key table.
For example, if you have a table of Hilton customers and an orders table, the column in the orders table could be a that references the column (which is the primary key) in the Hilton customers table.
SQL Question 6: Find the average capacity utilization of Hilton hotels
As an analyst for Hilton, you're tasked with finding out the average occupancy rate for all Hilton hotels on a monthly basis in 2021. You're given two tables, and . The table includes details about each hotel, including their total room count. The table includes details about each booking, such as , , , and .
Example Input:
| hotel_id | hotel_name | total_rooms |
|---|---|---|
| 1 | Hilton NYC | 1000 |
| 2 | Hilton LA | 800 |
| 3 | Hilton SF | 700 |
Example Input:
| booking_id | hotel_id | check_in_date | check_out_date |
|---|---|---|---|
| 92938 | 1 | 02/01/2021 | 02/05/2021 |
| 30912 | 1 | 03/05/2021 | 03/15/2021 |
| 48732 | 2 | 01/15/2021 | 01/17/2021 |
| 28929 | 2 | 04/01/2021 | 04/05/2021 |
| 36364 | 3 | 03/01/2021 | 03/03/2021 |
Your result should show the average occupancy rate of each Hilton hotel on a monthly basis in 2021.
Example Output:
| month | hotel_id | avg_occupancy_rate |
|---|---|---|
| 02 | 1 | 12% |
| 03 | 1 | 16% |
| 01 | 2 | 8% |
| 04 | 2 | 12% |
Answer:
Since PostgreSQL does not have a function that other SQL dialects have, we must manually subtract dates to get the length of stay per booking. We then sum those lengths, group by and , and divide by the total room count for the month to get the average occupancy rate.
This query will provide the average occupancy rate of each Hilton hotel per month in 2021, calculated as the total number of booked days divided by the total number of available rooms.
To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for averaging metrics over a time period or this Facebook Active User Retention Question which is similar for monthly utilization calculation.
SQL Question 7: How is a foreign key different from a primary key in a database?
To explain the difference between a primary key and foreign key, let's start with some data from Hilton's marketing analytics database which stores data from Google Ads campaigns:
:
| ad_id | campaign_id | keyword | click_count |
|---|---|---|---|
| 1 | 100 | Hilton pricing | 10 |
| 2 | 100 | Hilton reviews | 15 |
| 3 | 101 | Hilton alternatives | 7 |
| 4 | 101 | buy Hilton | 12 |
In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.
could be a foreign key. It references the of the Google Ads campaign that each ad belongs to, establishing a relationship between the ads and their campaigns. This foreign key allows you to easily query the table to find out which ads belong to a specific campaign, or to find out which campaigns a specific ad belongs to.
It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the ad group that each ad belongs to, and the of the Google Ads account that the campaigns belong to.
SQL Question 8: Analyzing Click-Through Rates for the Hilton Homepage
Assume you are a data analyst for Hilton Hotels. The marketing department wants to understand how effective different elements on Hilton's homepage are at driving users to click on hotel deals. Each row in the table represents a click event, with fields for the user ID, the time of the click, and the element of the homepage that was clicked. Each row in the table represents a hotel deal that was clicked on, with fields for the user ID, the time of the click, and the hotel deal ID.
Calculate the click-through rate (CTR) for each homepage element. CTR is defined as the number of unique users who clicked on a hotel deal after clicking on a homepage element divided by the total number of unique users who clicked on that homepage element.
Example Input:
| user_id | time_of_click | homepage_element |
|---|---|---|
| doria | 12:01 PM | slideshow |
| remus | 12:03 PM | hotspot |
| remus | 01:20 PM | slideshow |
| lyla | 06:10 PM | CTA button |
| doria | 06:12 PM | CTA button |
Example Input
| user_id | time_of_click | hotel_deal_id |
|---|---|---|
| doria | 12:05 PM | 1 |
| remus | 03:10 PM | 2 |
| lyla | 06:15 PM | 3 |
Answer:
This query calculates the click-through rate for each homepage element by joining the table with the table on user ID and ensuring that the time of the hotel deal click is after the homepage click. Using the function ensures that we're only counting unique users for each homepage element. We cast to to ensure that a decimal value is returned for the click-through rate.
To solve a similar SQL interview question on DataLemur's free online SQL coding environment, solve this Facebook SQL Interview question:
SQL Question 9: Finding the Average Room Price by Hotel Location
Given a list of hotel bookings on Hilton platform, find out the average room price for each hotel location. Assume you have booking details which includes the price per night and the location of each Hilton hotel.
Sample data for table:
Example Input:
| booking_id | user_id | check_in_date | hotel_location | price_per_night |
|---|---|---|---|---|
| 1659 | 356 | 06/16/2022 00:00:00 | New York | 340 |
| 2890 | 984 | 06/22/2022 00:00:00 | Chicago | 220 |
| 3729 | 476 | 06/25/2022 00:00:00 | New York | 350 |
| 4901 | 127 | 07/14/2022 00:00:00 | Chicago | 230 |
| 5567 | 351 | 07/20/2022 00:00:00 | Chicago | 210 |
We want to present the results in a table that shows each hotel location and the corresponding average price per night.
Example Output:
| hotel_location | avg_price_per_night |
|---|---|
| New York | 345 |
| Chicago | 220 |
Answer:
Here is a PostgreSQL query to solve this problem:
The above query groups the booking data based on the field and then uses the function to find the average price per night for each location. The results are returned in ascending order by .
SQL Question 10: What does the SQL command do?
Similar to the and / operators, the PostgreSQL INTERSECT operator combines result sets of two or more statements into a single result set. However, only returns the rows that are in BOTH select statements.
For a concrete example, say you were on the Sales Analytics team at Hilton, and had data on sales leads exported from both HubSpot and Salesforce CRMs in two different tables. To write a query to analyze leads created after 2023 started, that show up in both CRMs, you would use the command:
How To Prepare for the Hilton SQL Interview
The best way to prepare for a Hilton SQL interview is to practice, practice, practice. Besides solving the above Hilton SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Netflix, Airbnb, and Amazon.
Each exercise has hints to guide you, detailed solutions and best of all, there's an online SQL code editor so you can instantly run your query and have it executed.
To prep for the Hilton SQL interview you can also be a great idea to practice interview questions from other hospitality and restaurant companies like:
- PENN Entertainment SQL questions
- MGM Resorts SQL questions
- Darden Restaurants SQL questions
- Chipotle SQL questions
However, if your SQL skills are weak, don't worry about jumping right into solving questions – refresh your SQL knowledge with this SQL tutorial for Data Analytics.
This tutorial covers things like RANK() window functions and advantages of CTEs vs. subqueries – both of which show up often in Hilton interviews.
Hilton Worldwide Holdings Data Science Interview Tips
What Do Hilton Data Science Interviews Cover?
Besides SQL interview questions, the other topics covered in the Hilton Data Science Interview include:
- Probability & Stats Questions
- Coding Questions in Python or R
- Data Case Study Questions
- Machine Learning Questions
- Behavioral Questions based on Hilton culture and values
How To Prepare for Hilton Data Science Interviews?
To prepare for Hilton Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from Microsoft, Amazon & startups
- a refresher covering Python, SQL & ML
- over 1000+ 5-star reviews on Amazon
Don't ignore the behavioral interview – prepare for it using this guide on acing behavioral interviews.