9 Ares Management SQL Interview Questions (Updated 2024)
Data Analysts and Data Engineers at Ares Management write SQL for analyzing financial datasets and managing investment portfolios. That's the reason behind why Ares Management evaluates jobseekers on SQL interview problems.
So, to help you practice, here's 9 Ares Management SQL interview questions – can you solve them?
9 Ares Management SQL Interview Questions
SQL Question 1: Analyze Portfolio Performance
Ares Management is interested in analyzing the performance of their managed portfolios. They want to understand the quarter-over-quarter change in their portfolios' values. Write a SQL query to find out the quarter over quarter change in portfolio values. Assume that the company has a table and a table.
Example Input:
| portfolio_id | portfolio_name |
|---|---|
| 100 | Equity Focus |
| 200 | Real Estate Fund |
| 300 | Global Opportunities |
Example Input:
| portfolio_id | quarter | year | value |
|---|---|---|---|
| 100 | 1 | 2021 | 2000000 |
| 200 | 1 | 2021 | 3500000 |
| 300 | 1 | 2021 | 1500000 |
| 100 | 2 | 2021 | 2100000 |
| 200 | 2 | 2021 | 3700000 |
| 300 | 2 | 2021 | 1750000 |
| 100 | 3 | 2021 | 2050000 |
| 200 | 3 | 2021 | 3900000 |
| 300 | 3 | 2021 | 1800000 |
Answer:
This query calculates the quarter over quarter (qoq) change for each portfolio managed by Ares Management. The query first joins the and tables based on . Then it calculates the qoq change. This is done by taking the difference of the portfolio values between the current and previous quarters (obtained using the LAG window function), divided by the value of the previous quarter. The PARTITION BY clause ensures that calculations are done for each portfolio separately.
To practice a similar window function question on DataLemur's free online SQL code editor, try this Google SQL Interview Question:
SQL Question 2: Employees Earning More Than Managers
Suppose there was a table of Ares Management employee salary data. Write a SQL query to find all employees who earn more than their direct manager.
Ares Management 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 solution above is hard to understand, you can find a step-by-step solution with hints here: Employee Salaries Higher Than Their Manager.
SQL Question 3: What's the major difference between and ?
The clause works similarly to the clause, but it is used to filter the groups of rows created by the clause rather than the rows of the table themselves.
For example, say you were analyzing Ares Management sales data:
This query retrieves the total sales for all products in each region, and uses the clause to only sales made after January 1, 2023. The rows are then grouped by region and the clause filters the groups to include only those with total sales greater than $500k.
Check out the Ares Management Career page and see what role might be best for you!
SQL Question 4: Portfolio Financial Analysis
Suppose Ares Management wishes to analyze their financial portfolios. They manage a variety of assets across multiple portfolio managers. Each manager can run one or more portfolios, invested in multiple assets such as bonds, equities, etc. Additionally, the value of these assets fluctuates over time. Create a database schema to handle this situation. Write an SQL query to calculate the current total value of each portfolio.
Example Input:
| portfolio_id | manager_id | asset_id | acquisition_date | acquired_units |
|---|---|---|---|---|
| 001 | 001 | A1 | 01/01/2020 | 1000 |
| 002 | 001 | B1 | 01/03/2020 | 2000 |
| 003 | 002 | C1 | 01/05/2020 | 1500 |
| 004 | 002 | A1 | 01/07/2020 | 3000 |
| 005 | 003 | B1 | 01/02/2020 | 500 |
Example Input:
| asset_id | valuation_date | unit_value |
|---|---|---|
| A1 | 09/01/2022 | 5.00 |
| B1 | 09/01/2022 | 10.00 |
| C1 | 09/01/2022 | 8.00 |
Answer:
This query first joins the and tables on the column. Then, it filters for the most recent valuation date for each asset in the table. Next, it calculates the current value of assets in each portfolio by multiplying the most recent unit values with the acquired number of units. Finally, it groups by the to calculate the current total value of each portfolio.
SQL Question 5: What is a primary key?
A primary key is a special type of column or set of columns in a database table that is used to identify each row in the table. It helps to ensure that all the rows are distinct and prevents null values. Additionally, primary keys play a crucial role in maintaining the accuracy of the data by making sure that there are no duplicate rows. They are also used to establish relationships between tables.
To create a primary key in a SQL database, you can use the constraint. For example, in the table , the column is the primary key.
SQL Question 6: Filter Investments By Client and Sector
Question: Ares Management wants to review their investments for a specific client and within a particular sector. Can you write a query to filter the investments table for data where the client ID equals 10001 and the sector is Real Estate?
Let's suppose the table looks like this:
Example Input:
| investment_id | client_id | investment_date | amount | sector |
|---|---|---|---|---|
| 8192 | 10001 | 04/06/2020 | 2000000 | Real Estate |
| 7169 | 10002 | 03/07/2021 | 1500000 | Consumer Goods |
| 5283 | 10003 | 02/28/2022 | 1000000 | Technology |
| 4629 | 10001 | 07/11/2022 | 5000000 | Real Estate |
| 3982 | 10004 | 08/08/2022 | 2500000 | Healthcare |
Expected output should look like this:
Example Output:
| investment_id | client_id | investment_date | amount | sector |
|---|---|---|---|---|
| 8192 | 10001 | 04/06/2020 | 2000000 | Real Estate |
| 4629 | 10001 | 07/11/2022 | 5000000 | Real Estate |
Answer:
The query uses the WHERE clause to filter the rows where the equals and equals .
In PostgreSQL, the query would look as follows:
This query will return all records from the investments table where the client ID is 10001 and the investment sector is Real Estate. It allows us to focus specifically on investments related to this particular client and sector.
SQL Question 7: Can you explain the concept of a constraint in SQL?
SQL constraints are used to specify rules for the data in a table. They can be applied to single or multiple fields in a table when the table is created, or after the table has been created using the ALTER TABLE command.
For example, say you had a database that stores ad campaign data from Ares Management's Google Analytics account.
Here's what some constraints could look like:
SQL Question 8: Analyzing Click-Through Rates for Ares Management Digital Ads
Ares Management is interested in analyzing their digital ad campaigns. They measure the success of these campaigns by examining Click-Through Rates (CTR). CTR is calculated as the number of click-throughs divided by the number of ad Impressions, represented as a percentage.
For every ad shown, Ares records whether or not it was clicked, the campaign it was part of, and the date of the impression. Given this information, write a SQL query to calculate the CTR for each campaign on a monthly basis.
Example Input:
| impression_id | date | campaign_id | was_clicked |
|---|---|---|---|
| 101 | 2022-01-01 | 1 | True |
| 102 | 2022-01-02 | 1 | False |
| 103 | 2022-01-03 | 1 | True |
| 104 | 2022-01-04 | 2 | False |
| 105 | 2022-02-01 | 2 | True |
| 106 | 2022-02-02 | 2 | True |
| 107 | 2022-02-03 | 2 | False |
Answer:
This query first extracts the month from the date of each ad impression. It then groups the data by both the month and the campaign_id. For each group, it calculates the total number of impressions (which is simply the count of rows within the group) and the total number of clicks (using a CASE statement to add up all the instances where was_clicked is true). It calculates CTR as the ratio of clicks to impressions, converted to a percentage.
The result is a monthly breakdown of the CTR for each campaign. This information can be incredibly valuable for Ares Management, as it allows them to monitor the performance of their ad campaigns over time, making optimizing their digital advertising strategy easier.
To practice a similar problem about calculating rates, solve this SQL interview question from TikTok on DataLemur's interactive SQL code editor:
SQL Question 9: Find customers with a specific pattern in their name
Ares Management is a leading global alternative investment manager operating three integrated businesses across credit, private equity, and real estate investments. In their customer records database, they have a table named 'customers' which contains columns: 'customer_id', 'first_name', 'last_name', 'email', and 'date_of_birth'.
Could you construct a SQL query to fetch customers whose first name starts with 'Ares'?
Example Input:
| customer_id | first_name | last_name | date_of_birth | |
|---|---|---|---|---|
| 1 | Ares Smith | Smith | ares.smith@gmail.com | 1982-10-12 |
| 2 | John Doe | Doe | john.doe@mail.com | 1990-05-20 |
| 3 | Ares Johnson | Johnson | ares.johnson@gmail.com | 1987-03-14 |
| 4 | Mary Jane | Jane | mary.jane@mail.com | 1984-05-21 |
| 5 | Ares Thompson | Thompson | ares.thompson@gmail.com | 1992-12-15 |
Answer:
This PostgreSQL query uses the SQL keyword with a wildcard '%' character. The query fetches the records of customers whose first names start with 'Ares'. The '%' character is a wildcard in SQL that matches any sequence of characters. Using 'Ares%' in the WHERE clause will match any string that starts with 'Ares'. As a result, all customers with a first name starting with 'Ares' are returned in the query results.
How To Prepare for the Ares Management SQL Interview
The best way to prepare for a SQL interview, besides making sure you have strong SQL fundamentals, is to practice a ton of real SQL questions that were asked in recent job interviews.
In addition to solving the earlier Ares Management SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Microsoft, Google, and Facebook.
Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there is an online SQL coding environment so you can right online code up your SQL query answer and have it checked.
To prep for the Ares Management SQL interview it is also helpful to solve interview questions from other investment management and private equity companies like:
In case your SQL foundations are weak, forget about going right into solving questions – go learn SQL with this DataLemur SQL Tutorial.
This tutorial covers things like rank window functions and WHERE vs. HAVING – both of these show up routinely in Ares Management interviews.
Ares Management Data Science Interview Tips
What Do Ares Management Data Science Interviews Cover?
Beyond writing SQL queries, the other types of problems to practice for the Ares Management Data Science Interview include:
- Statistics and Probability Questions
- Python Pandas or R Coding Questions
- Business Sense and Product-Sense Questions
- Machine Learning and Predictive Modeling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Ares Management Data Science Interviews?
To prepare for Ares Management Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions sourced from Microsoft, Amazon & startups
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