8 Boston Properties SQL Interview Questions (Updated 2024)
At Boston Properties, SQL is used for analyzing property and tenant data for insights and manipulating huge property management databases for predictive analytics. That's the reason behind why Boston Properties typically asks SQL problems in interviews for Data Science and Data Engineering positions.
So, to help you prepare, we've curated 8 Boston Properties SQL interview questions – able to solve them?
8 Boston Properties SQL Interview Questions
SQL Question 1: Identify Top Renters from Boston Properties
Boston Properties is a company that rents properties across different locations in Boston. They categorize the renters into different classes based on the total rent they pay yearly. The task here is to identify 'VIP customers' who are classified as renters that pay more than $100,000 in rents annually. With given datasets for customer information and rental transactions, write an SQL script to retrieve the list of VIP Customers.
Example Input:
| renter_id | first_name | last_name | registered_date | |
|---|---|---|---|---|
| 6171 | John | Doe | john.doe@example.com | 01/05/2022 |
| 7802 | Jane | Smith | jane.smith@example.com | 10/15/2021 |
| 5293 | Larry | Johnson | larry.johnson@example.com | 12/08/2021 |
| 6352 | Alice | Brown | alice.brown@example.com | 08/20/2021 |
| 4517 | Robert | Miller | robert.miller@example.com | 11/05/2021 |
Example Input:
| transaction_id | renter_id | property_id | rent_amount | transaction_date |
|---|---|---|---|---|
| 2901 | 6171 | 100 | 25000 | 01/10/2022 |
| 9723 | 7802 | 200 | 80000 | 01/15/2022 |
| 4372 | 5293 | 300 | 90000 | 01/20/2022 |
| 3051 | 6352 | 400 | 45000 | 01/25/2022 |
| 2419 | 6171 | 500 | 80000 | 02/01/2022 |
Answer:
The above SQL statement first combines data from the two tables based on renter_id. It then groups these results by renter_id and sums the rent_amount for each renter. The HAVING clause filters out those renters whose total rent is greater than $100,000, which are considered VIP customers.
To work on a similar customer analytics SQL question where you can code right in the browser and have your SQL query instantly executed, try this Walmart SQL Interview Question:
SQL Question 2: 2nd Largest Salary
Given a table of Boston Properties employee salaries, write a SQL query to find the 2nd highest salary at the company.
Boston Properties Example Input:
| employee_id | salary |
|---|---|
| 1 | 2500 |
| 2 | 800 |
| 3 | 1000 |
| 4 | 1200 |
Example Output:
| second_highest_salary |
|---|
| 1200 |
Solve this problem and run your code right in DataLemur's online SQL environment:
Answer:
You can find a detailed solution here: 2nd Highest Salary.
Read about Boston Properties 2023 Sustainabiltiy and impact KPI sheet.
SQL Question 3: Can you explain the purpose of UNION?
is used to combine the output of multiple statements into one big result!
For a concrete example, say you were doing an HR Analytics project for Boston Properties and needed to analyze both Boston Properties's employees and contractors who were hired after 2022 started. You could use in the following way:
SQL Question 4: Analyzing Rental Payments Over Time
Given a table of rental payments made by tenants in Boston Properties, write a SQL query to find the total monthly rent collected per building over the course of a year, along with the month-by-month percentage increase or decrease from the previous month.
Example Input:
| rental_id | tenant_id | building_id | payment_date | amount |
|---|---|---|---|---|
| 5124 | 101 | B001 | 2022-01-01 | 2000 |
| 6751 | 102 | B001 | 2022-01-01 | 1900 |
| 7128 | 103 | B002 | 2022-01-01 | 2100 |
| 5125 | 101 | B001 | 2022-02-01 | 2000 |
| 6752 | 102 | B001 | 2022-02-01 | 1900 |
| 7129 | 103 | B002 | 2022-02-01 | 2100 |
Example Output:
| month | building_id | total_rent | percentage_change |
|---|---|---|---|
| 1 | B001 | 3900 | NULL |
| 1 | B002 | 2100 | NULL |
| 2 | B001 | 3900 | 0.00 |
| 2 | B002 | 2100 | 0.00 |
Answer:
In this query, we first create a base CTE (Common Table Expression) to summarize the monthly total rent per building. Next, we create a calc CTE where we get the previous month's total rent by using the window function LAG. We then calculate the percentage change in the final SELECT statement. The window function allows us to compare the value from the current row (total_rent) with the value from a previous row (previous_total_rent) inside each partition (building_id), thus enabling us to compute the month-over-month change in rent.
To solve a similar window function question on DataLemur's free interactive coding environment, solve this Google SQL Interview Question:
SQL Question 5: When would you use the / commands in SQL?
For a tangible example of in PostgreSQL, suppose you were doing an HR Analytics project for Boston Properties, and had access to Boston Properties's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables.
You could use operator to find all contractors who never were a employee using this query:
Note that is available in PostgreSQL and SQL Server, while is the equivalent operator which is available in MySQL and Oracle (but don't worry about knowing which RDBMS supports which exact commands since Boston Properties interviewers aren't trying to trip you up on memorizing SQL syntax).
SQL Question 6: Filtering Boston Properties' Leased Office Spaces
As a data analyst at Boston Properties, you are charged with analyzing the database of properties currently leased out. You've been tasked with generating a subset of properties which meet the following conditions: they should be office properties located in Boston with a lease end date after December 31, 2023, and the tenant should not be a government agency.
Boston Properties have the following tables:
Example Input:
| property_id | property_type | location |
|---|---|---|
| 1 | Office | Boston |
| 2 | Retail | Boston |
| 3 | Office | New York |
| 4 | Office | Boston |
| 5 | Residential | Boston |
Example Input:
| lease_id | property_id | tenant_type | lease_end_date |
|---|---|---|---|
| 1 | 1 | Private | 12/31/2024 |
| 2 | 2 | Government | 12/31/2023 |
| 3 | 1 | Private | 12/31/2020 |
| 4 | 4 | Government | 12/31/2025 |
| 5 | 4 | Private | 01/01/2024 |
Answer:
In this PostgreSQL query, we're joining and tables, and using the WHERE clause to filter the joined table as per our conditions. We've used the 'AND' and '<>' operator to ensure that all conditions need to be met and to exclude the rows with the tenant type as 'Government', respectively.
SQL Question 7: 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 Boston Properties 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 INNER JOIN 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 8: Finding the Property with Highest Lease Amount
Suppose the leasing department at Boston Properties wants to understand their lease performance. They want to know which property had the highest total lease amount in each year.
Here are some sample tables:
Example Input:
| property_id | property_name | property_location |
|---|---|---|
| 101 | Marina Plaza | San Francisco |
| 102 | Embarcadero Center | San Francisco |
| 103 | Prudential Tower | Boston |
Example Input:
| lease_id | property_id | tenant_id | start_date | end_date | lease_amount |
|---|---|---|---|---|---|
| 2001 | 101 | 4001 | 01/01/2022 00:00:00 | 12/31/2022 23:59:59 | 15000 |
| 2002 | 101 | 4002 | 10/01/2022 00:00:00 | 09/30/2023 23:59:59 | 12000 |
| 2003 | 102 | 4003 | 05/01/2022 00:00:00 | 04/30/2023 23:59:59 | 20000 |
| 2004 | 103 | 4004 | 07/01/2022 00:00:00 | 06/30/2023 23:59:59 | 20000 |
Answer:
In this example query, we first join the table with the table on the column. Then, we group by year () extracted from the lease and , and sum the for each group. The function paired with keyword partitions the result set by and finds the property with the highest total lease amount for each year.
Preparing For The Boston Properties SQL Interview
The best way to prepare for a Boston Properties SQL interview is to practice, practice, practice.
In addition to solving the above Boston Properties SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Google, Microsoft and Silicon Valley startups.
Each exercise has hints to guide you, full answers and best of all, there is an interactive coding environment so you can right in the browser run your query and have it executed.
To prep for the Boston Properties SQL interview you can also be helpful to solve SQL questions from other real estate and REIT companies like:
However, if your SQL foundations are weak, forget about diving straight into solving questions – go learn SQL with this DataLemur SQL tutorial.
This tutorial covers SQL concepts such as finding NULLs and joining multiple tables – both of which show up frequently during Boston Properties SQL assessments.
Boston Properties Data Science Interview Tips
What Do Boston Properties Data Science Interviews Cover?
In addition to SQL query questions, the other types of problems to prepare for the Boston Properties Data Science Interview include:
- AB Testing Questions
- Python or R Coding Questions
- Product Analytics Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Boston Properties Data Science Interviews?
To prepare for Boston Properties Data Science interviews read the book Ace the Data Science Interview because it's got:
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