10 Hyatt SQL Interview Questions (Updated 2024)
Hyatt employees rely on SQL queries to analyze guest booking trends, helping them identify peak travel times and popular room types that guests prefer. It also allows them to optimize hotel inventory management, ensuring they have the right number of rooms available to meet demand, this is the reason why Hyatt tests SQL coding questions in interviews for Data Analytics, Data Science, and Data Engineering jobs.
Thus, to help you prep for the Hyatt SQL interview, here’s 10 Hyatt Hotels SQL interview questions – can you solve them?
10 Hyatt Hotels SQL Interview Questions
SQL Question 1: Analyze Average Hotel Ratings per Month
Given a table of hotel reviews, write a SQL query to calculate the average star rating for each hotel per month. Assume that you're analyzing the data from a database associated with Hyatt Hotels Corporation.
The table schema is:
| review_id | user_id | submit_date | hotel_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2019/01/10 | 1001 | 5 |
| 7802 | 265 | 2019/02/15 | 2002 | 4 |
| 5293 | 362 | 2019/03/18 | 1001 | 3 |
| 6352 | 192 | 2019/02/26 | 2002 | 3 |
| 4517 | 981 | 2019/04/15 | 1001 | 4 |
The star column indicates the rate given for the hotel by a user in the scale of 1-5 where 5 is the best.
The output table schema is:
| mth | hotel_id | avg_stars |
|---|
is the month number (1- January, 2- February, etc.) when the review was submitted. Use PostgreSQL for the SQL query.
Answer:
This SQL query first extracts the month from the , then groups by both and to calculate the average star rating for each hotel per month. The resulting table will be ordered by first and then in descending order of to put the highest average rating for each month at the top.
Pro Tip: Window functions are a popular SQL interview topic, so practice all the window function problems on DataLemur
Explore Hyatt's newsroom to learn about their latest initiatives and how they are enhancing guest experiences across their hotels! Understanding Hyatt's developments can give you a glimpse into the hospitality trends that are shaping the future.
SQL Question 2: Top Department Salaries
Given a table of Hyatt employee salary information, write a SQL query to find the top 3 highest paid employees within each department.
Hyatt Example Input:
| employee_id | name | salary | department_id |
|---|---|---|---|
| 1 | Emma Thompson | 3800 | 1 |
| 2 | Daniel Rodriguez | 2230 | 1 |
| 3 | Olivia Smith | 2000 | 1 |
| 4 | Noah Johnson | 6800 | 2 |
| 5 | Sophia Martinez | 1750 | 1 |
| 8 | William Davis | 6800 | 2 |
| 10 | James Anderson | 4000 | 1 |
Example Input:
| department_id | department_name |
|---|---|
| 1 | Data Analytics |
| 2 | Data Science |
Example Output:
| department_name | name | salary |
|---|---|---|
| Data Analytics | James Anderson | 4000 |
| Data Analytics | Emma Thompson | 3800 |
| Data Analytics | Daniel Rodriguez | 2230 |
| Data Science | Noah Johnson | 6800 |
| Data Science | William Davis | 6800 |
Check your SQL query for this question and run your code right in DataLemur's online SQL environment:
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 hard to understand, you can find a step-by-step solution with hints here: Top 3 Department Salaries.
SQL Question 3: What's a database view, and what's their purpose?
Database views are created to provide customized, read-only versions of your data that you can query just like a regular table. So why even use one if they're so similar to a regular table?
Views are advantageous for several reasons:
- views allow you to create a simpler versions of your data for specific users (such as hiding extraneous columns/rows from business analysts since they're relics of the Data Engineering pipelines setup)
- views help you comply with data security requirements by hiding sensitive data from certain users (important for regulated industries like govermnet and healthcare!)
- views can improve performance for complicated queries by pre-computing the results and caching them in a view (which is often faster than re-executing the original query)
SQL Question 4: Hotel Room Occupancy Analysis
Suppose Hyatt, a global hospitality company, wants to optimize their room occupancy rate. They need to understand which type of rooms are usually occupied, and who are the frequent customers. They also want to know the average duration of a stay. They have asked you to pull the relevant data to help them answer these questions. You have the following three tables:
Table:
| room_id | type | capacity | price |
|---|---|---|---|
| 101 | Deluxe | 2 | 150 |
| 102 | Standard | 2 | 100 |
| 201 | Suite | 4 | 250 |
| 202 | Standard | 2 | 100 |
| 301 | Deluxe | 2 | 150 |
Table:
| customer_id | name | country |
|---|---|---|
| 1 | John Smith | USA |
| 2 | Maria Garcia | Mexico |
| 3 | Li Wei | China |
| 4 | Sara Watson | England |
| 5 | Mohamed Ali | Egypt |
Table:
| stay_id | customer_id | room_id | check_in_date | check_out_date |
|---|---|---|---|---|
| 6001 | 1 | 101 | 01/10/2022 | 04/10/2022 |
| 6002 | 2 | 102 | 03/10/2022 | 10/10/2022 |
| 6003 | 3 | 201 | 05/10/2022 | 08/10/2022 |
| 6004 | 4 | 202 | 01/10/2022 | 03/10/2022 |
| 6005 | 5 | 101 | 04/10/2022 | 07/10/2022 |
Write a PostgreSQL query to find the following for each type of room:
- Number of stays
- Average duration of a stay (in days)
- The name of the most frequent customer for each room type
Answer:
This query first calculates the total number of stays and the average duration of stays for each room type. Then, it calculates the number of stays for each customer for each room type. Lastly, it combines these results to give the desired output.
SQL Question 5: What distinguishes an inner join from a full outer join?
An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.
For a concrete example, imagine you had two database tables, an advertising campaigns table which had information on Google Ads keywords and how much was bid for each keyword, and a Hyatt sales table, which has data on how many products were sold and which Google Ads keyword drove that sale.
: retrieves rows from both tables where there is a match in the shared key or keys. For example, an between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.
: retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.
SQL Question 6: Analyzing Click-Through-Rates for Hyatt Hotel's Digital Campaigns
As part of Hyatt's digital marketing team, you have access to logs detailing actions taken by user's on Hyatt's website. These logs capture various actions, such as viewing a hotel room, clicking an ad, or booking a room. To make marketing decisions, the team frequently analyses the data looking at the click-through rates of digital ads and booking conversion rates from viewing a room to booking it. Given the below tables, can you write a query to report click-through rates for ads and booking conversion rates for each hotel?
Example Input:
| click_id | ad_id | user_id | click_time |
|---|---|---|---|
| 101 | AD1 | U87 | 08/01/2022 00:00:00 |
| 102 | AD1 | U65 | 08/02/2022 00:00:00 |
| 103 | AD2 | U87 | 08/03/2022 00:00:00 |
| 104 | AD2 | U86 | 08/04/2022 00:00:00 |
| 105 | AD3 | U65 | 08/05/2022 00:00:00 |
Example Input:
| view_id | user_id | view_time | hotel_id |
|---|---|---|---|
| 201 | U87 | 08/01/2022 00:01:00 | H1 |
| 202 | U65 | 08/02/2022 00:02:00 | H2 |
| 203 | U87 | 08/03/2022 00:03:00 | H2 |
| 204 | U86 | 08/04/2022 00:04:00 | H3 |
| 205 | U65 | 08/05/2022 00:05:00 | H1 |
Example Input:
| booking_id | user_id | booking_time | hotel_id |
|---|---|---|---|
| 301 | U87 | 08/01/2022 00:02:00 | H1 |
| 302 | U65 | 08/02/2022 00:03:00 | H2 |
| 303 | U87 | 08/03/2022 00:04:00 | H2 |
Answer:
This SQL query first aggregates number of room views and number of bookings for each hotel, and computes the booking conversion rate for each hotel. It then aggregates the number of ads displayed and the number of ad clicks, and computes the click-through rate for each ad. The results are joined together to give a comprehensive view of the performance of each hotel's marketing efforts.
To practice another question about calculating rates, solve this TikTok SQL Interview Question on DataLemur's online SQL code editor:
SQL Question 7: How can you identify duplicates in a table? Do have any other approaches?
One way to find duplicates is to use a clause and then use to find groups.
You could also use the operator:
SQL Question 8: Calculate the Average Rating per Hotel per Month
As a data analyst at Hyatt, your task is to analyze the customer service feedback from guests of Hyatt. Write a SQL query that returns the average service rating each month for every hotel in the Hyatt chain.
Example Input:
| feedback_id | customer_id | submission_date | hotel_id | rating |
|---|---|---|---|---|
| 421 | 101 | 01/10/2022 00:00:00 | A1 | 4 |
| 356 | 254 | 02/15/2022 00:00:00 | A1 | 5 |
| 348 | 365 | 03/20/2022 00:00:00 | B2 | 4 |
| 597 | 192 | 04/11/2022 00:00:00 | C3 | 2 |
| 618 | 847 | 05/16/2022 00:00:00 | B2 | 1 |
Example Output:
| month | hotel | avg_rating |
|---|---|---|
| 1 | A1 | 4.00 |
| 2 | A1 | 5.00 |
| 3 | B2 | 4.00 |
| 4 | C3 | 2.00 |
| 5 | B2 | 1.00 |
Answer:
In the above PostgreSQL query, we extract the month from the column and use this data along with the in the clause. The function is then used to compute the average rating for each group. The result is ordered first by and then by the month.
SQL Question 9: Filter Hyatt Customers Residing in a Specific City
At Hyatt Corporation, a hotels and resorts chain, you have a database of customer records. Your task is to find all the customers who are from cities whose names start with "San", e.g., "San Francisco", "San Diego", "San Bernardino", etc.
Example Input:
| customer_id | first_name | last_name | address | city | zip_code |
|---|---|---|---|---|---|
| 10001 | Sam | Jones | 9300 N Yale Ave | San Francisco | 94134 |
| 10002 | John | Smith | 4500 Cherry St | Denver | 80246 |
| 10003 | Jane | Doe | 2145 Sheridan Boulevard | San Diego | 92101 |
| 10004 | Bob | Brown | 6200 N Sheridan Rd | Chicago | 60660 |
| 10005 | Susan | Williams | 3440 N Broadway St | San Bernardino | 92405 |
Your job is to write a query that will return the , , and of customers residing in cities that start with "San".
Answer:
The above PostgreSQL query checks for records (, , , ) in the table where the begins with the substring "San". The keyword followed by 'San%' ensures that we are filtering for those city names that start with 'San' irrespective of what follows it. The '%' character in SQL's operator is a wildcard that matches zero, one, or multiple characters.
Example Output:
| customer_id | first_name | last_name | city |
|---|---|---|---|
| 10001 | Sam | Jones | San Francisco |
| 10003 | Jane | Doe | San Diego |
| 10005 | Susan | Williams | San Bernardino |
The result of the query will display customers who are from cities starting with "San".
SQL Question 10: What is a database index, and what are the different types of indexes?
A database index is a data structure that provides a quick lookup of data in a column or columns of a table.
There are several types of indexes that can be used in a database:
- Primary index: a unique identifier is used to access the row directly.
- Unique index: used to enforce the uniqueness of the indexed columns in a table.
- Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
- Clustered index: determines the physical order of the data in a table
How To Prepare for the Hyatt SQL Interview
The key to acing a Hyatt SQL interview is to practice, practice, and then practice some more! Beyond just solving the above Hyatt SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.
Each interview question has multiple hints, fully explained answers along with a discussion board to see how others solved it and best of all, there's an interactive coding environment so you can right in the browser run your SQL query and have it checked.
To prep for the Hyatt SQL interview you can also be a great idea to practice interview questions from other hospitality and restaurant companies like:
- Topgolf SQL questions
- Travel + Leisure SQL questions
- Light & Wonder SQL questions
- Brinker International SQL questions
In case your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this interactive SQL tutorial.
This tutorial covers SQL topics like using wildcards with LIKE and ordering data – both of which show up often in SQL job interviews at Hyatt.
Hyatt Hotels Data Science Interview Tips
What Do Hyatt Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems to practice for the Hyatt Data Science Interview include:
- Statistics & AB Testing Questions
- Python or R Coding Questions
- Business Sense and Product-Sense Questions
- ML Interview Questions
- Behavioral Questions centered on Hyatt values & principles
How To Prepare for Hyatt Data Science Interviews?
To prepare for Hyatt Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from Google, Microsoft & tech startups
- a refresher on Python, SQL & ML
- over 1000+ 5-star reviews on Amazon
Don't forget about the behavioral interview – prep for that using this list of common Data Scientist behavioral interview questions.