10 Blackstone SQL Interview Questions (Updated 2024)

Blackstone employees use SQL daily for analyzing financial data patterns and managing real estate investment databases. That's the reason behind why Blackstone typically asks SQL questions in interviews for Data Analyst, Data Science, and BI jobs.

To help you prep for the Blackstone SQL interview, here's 10 Blackstone SQL interview questions – scroll down to start solving them!

10 Blackstone SQL Interview Questions

SQL Question 1: Identify VIP Customers

The Real Estate team at Blackstone is interested to know their "VIP customers". These customers are defined as those who have made frequent transactions over $5 million in the past two years. Provide a list of VIP customers, sorted by their total transaction amount in descending order.

Example Input:

Example Input:

Answer:

The above PostgreSQL query joins the and table on and applies a filter for transactions that are over $5 million and are in the past 2 years. It then groups by the to sum up the for each customer. The results are ordered in descending order based on the sum of the . Thus, generating a list of VIP customers sorted by their total transaction amounts.

To practice a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft Teams Power User SQL Interview Question:

SQL Question 2: Employees Earning More Than Managers

Assume there was a table of Blackstone employee salaries. Write a SQL query to find all employees who earn more than their direct manager.

Blackstone Example Input:

Example Output:

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

Try this problem 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 tough, you can find a detailed solution with hints here: Employee Salaries Higher Than Their Manager.

Read about how Data Science empower's Blackstone's investments and operations.

SQL Question 3: What are stored procedures, and why are they useful?

Stored procedures are a lot like functions in programming. They're used to encapsulate and organize business logic into one unit of code, and they can accept multiple input parameters and return multiple output values.

For example, if you were a Data Analyst at Blackstone working on a HR analytics project, you might create a stored procedure to calculate the average salary for a given department:

To call this stored procedure and find the average salary for the Data Analytics department you'd write the following query:

SQL Question 4: Calculate the Monthly Average Rating of Products

You're a data analyst at Blackstone, a leading investment firm. The company recently launched a number of new products and is interested in understanding how customers rate these products over time.

You have a table containing customer reviews which includes the following information:

• : unique identifier of the review
• : unique identifier of the user who submitted the review
• : The date the review was submitted
• : unique identifier of the product
• : The star rating of the product, on a scale from 1 (worst) to 5 (best).

Your task is to write a SQL query that will return a new table with columns for the month of review submission (), , and the average star rating () for each product for each month. Assume that the current date is 26th August, 2022.

Example Input:

Expected Output:

Answer:

In the SQL statement above, we first use PostgreSQL's function to get the month from the column. Then, we group the data by the extracted month and . Finally, we calculate the average for each group and order the results by month and product ID.

For more window function practice, try this Uber SQL Interview Question on DataLemur's online SQL code editor:

SQL Question 5: Can you explain what SQL constraints are, and why they are useful?

Constraints are used to specify the rules concerning data in the table. It can be applied for single or multiple fields in an SQL table during the creation of the table or after creating using the ALTER TABLE command. The constraints are:

Say you were storing sales analytyics data from Blackstone's CRM inside a database. Here's some example constraints you could use:

• PRIMARY KEY constraint: You might use a PRIMARY KEY constraint to ensure that each record in the database has a unique identifier. For example, you could use the "opportunity_id" field as the primary key in the "opportunities" table.

• FOREIGN KEY constraint: You might use a FOREIGN KEY constraint to link the data in one table to the data in another table. For example, you could use a foreign key field in the "opportunities" table to reference the "account_id" field in the "accounts" table.

• NOT NULL constraint: You might use a NOT NULL constraint to ensure that a field cannot contain a NULL value. For example, you could use a NOT NULL constraint on the "opportunity_name" field in the "opportunities" table to ensure that each opportunity has a name.

• UNIQUE constraint: You might use a UNIQUE constraint to ensure that the data in a field is unique across the entire table. For example, you could use a UNIQUE constraint on the "email" field in the "contacts" table to ensure that each contact has a unique email address.

• CHECK constraint: You might use a CHECK constraint to ensure that the data in a field meets certain conditions. For example, you could use a CHECK constraint to ensure that the "deal_probability" field in the "opportunities" table is a value between 0 and 100.

• DEFAULT constraint: You might use a DEFAULT constraint to specify a default value for a field. For example, you could use a DEFAULT constraint on the "stage" field in the "opportunities" table to set the default value to "prospecting"

SQL Question 6: Portfolio Analysis

As a Data Engineer for Blackstone, one of the major tasks is to manage the database for the enormous amount of financial portfolios held by the company. A business problem faced by the company is to identify the performance of their portfolios. They want to understand the average monthly returns for each portfolio over the last year to analyse their profitability.

Given the database tables of Portfolios and Portfolio_Returns as provided below, could you help them to get monthly average returns for each portfolio?

Example Input:

Example Input:

Answer:

This query first does an INNER JOIN between Portfolios and Portfolio_Returns tables on the portfolio_id field. Then, it groups the data by portfolio_name and month_year, calculates the average returns for every group. This will result in monthly average returns for each portfolio.

SQL Question 7: Can you give some examples of when denormalization might be a good idea?

Normalization can reduce redundancy and improve performance and flexibility in a database.

By dividing larger tables into smaller, more specific ones linked by foreign keys, it is often possible to improve query speed. Note: it is not always the case that query speed will be improved due to costly nature of joins. Still, we think normalization is a good idea because it can also increase flexibility by making it easier to alter individual tables without affecting others, which can be useful for adapting Blackstone's database to ever-changing business needs.

SQL Question 8: Average Investment Size by Sector

As a data analyst at Blackstone, you are tasked to find out the average size of investments made by Blackstone in various sectors for the year 2021. Given two tables which contains information on each investment made and which links each company with its corresponding sector, write a SQL query to compute this statistic.

Example Input

Example Input

Answer:

This query calculates the average investment sizes by sector for the year 2021. It uses the function to compute the average investment size, clause to combine the and tables, and clause to group the results by sector. The condition ensures that only the investments made in the year 2021 are taken into account.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating metrics across different categories or this Google Median Google Search Frequency Question which is similar for generating aggregated statistics for specific time periods.

SQL Question 9: Calculate the click-through-conversion rate in Blackstone's product marketing

Blackstone is a company that sells information products online. They routinely engage in digital advertising to drive traffic to their products and measure the success of these campaigns through multiple metrics. One such key metric is the click-through-conversion rate, which measures the percentage of users who click on an advertisement and then proceed to add the product to the cart.

We have the following tables:

Example Input:

Example Input:

Answer:

The query calculates the number of distinct users who clicked on the ad for each product per day ( CTE) and the number who added the product to their cart ( CTE). Then, it joins these two results on the date and product_id and computes the conversion rate for each day for each product. The conversion rate is represented as a percentage.

To solve a similar SQL problem on DataLemur's free interactive coding environment, try this SQL interview question asked by Facebook:

SQL Question 10: What's the purpose of the function in SQL?

The function accepts an unlimited number of input arguments, and returns the first argument from that list which isn't null.If all input arguments are null, will return null too.

For example, suppose you had data on Blackstone salespeople, and the amount of deals they closed. This data was exported from a 3rd-party system CRM, which exports a value if the salesperson didn't close any deals.

To get rid of these NULLs, and replace them with zero's (so you can do some further analytics like find the average number of closed deals), you would use the function as follows:

You'd get the following output:

Blackstone SQL Interview Tips

The key to acing a Blackstone SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Blackstone SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Google, Uber, and Microsoft.

Each DataLemur SQL question has hints to guide you, step-by-step solutions and crucially, there is an online SQL code editor so you can instantly run your SQL query and have it graded.

To prep for the Blackstone SQL interview you can also be wise to solve interview questions from other investment management and private equity companies like:

• BlackRock SQL questions

• U.S. Bancorp SQL questions

• KKR SQL questions

• CBRE Group SQL questions

But if your SQL skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Analytics.

This tutorial covers things like using ORDER BY and filtering groups with HAVING – both of these come up frequently during SQL interviews at Blackstone.

Blackstone Data Science Interview Tips

What Do Blackstone Data Science Interviews Cover?

In addition to SQL query questions, the other topics covered in the Blackstone Data Science Interview are:

• Probability & Statistics Questions
• Python or R Programming Questions
• Product Metrics Interview Questions
• ML Modelling Questions
• Resume-Based Behavioral Questions

How To Prepare for Blackstone Data Science Interviews?

The best way to prepare for Blackstone Data Science interviews is by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from Facebook, Google & startups
• A Refresher covering Stats, ML, & Data Case Studies
• Amazing Reviews (1000+ 5-star reviews on Amazon)