8 Franklin Resources SQL Interview Questions (Updated 2024)
At Franklin Templeton Investments, SQL is typically used for analyzing financial data trends and optimizing investment portfolio performance That's the reason behind why Franklin Resources frequently asks SQL questions in interviews for Data Science, Analytics, and & Data Engineering jobs.
To help you prepare for the Franklin Resources SQL interview, here’s 8 Franklink Templeton Investments SQL interview questions in this blog.
8 Franklink Templeton Investments SQL Interview Questions
SQL Question 1: Identify the VIP Users
Franklin Resources would like to identify the VIP users, the top 10 users with the most transactions, based on their transaction table. The VIP users are the ones that transact the most frequently in the year 2022. Create a SQL query that identifies these users, and sorts them in descending order of their transaction count.
Example Input:
| transaction_id | user_id | transaction_date | amount |
|---|---|---|---|
| 101 | 123 | 01/08/2022 | 50.50 |
| 102 | 456 | 02/08/2022 | 105.99 |
| 103 | 123 | 02/15/2022 | 75.25 |
| 104 | 789 | 03/06/2022 | 120.49 |
| 105 | 456 | 03/15/2022 | 89.99 |
| 106 | 123 | 04/22/2022 | 59.95 |
| 107 | 456 | 04/28/2022 | 115.00 |
| 108 | 123 | 05/08/2022 | 150.00 |
| 109 | 456 | 05/22/2022 | 110.75 |
| 110 | 789 | 06/15/2022 | 500.00 |
Answer:
In PostgreSQL, we can use a combination of COUNT() and GROUP BY to identify these users. Here is the query:
This query first filters transactions to keep only those happened in the year 2022. The GROUP BY statement combined with the COUNT(*) function counts the number of transactions for each user. Finally, users are sorted in a descending order according to their transaction count, and only the top 10 are kept with the help of the LIMIT statement.
Note: The transaction_date is presumed to be a timestamp or date datatype for the YEAR function to work properly.
To practice a similar customer analytics SQL question where you can code right in the browser and have your SQL solution instantly graded, try this Walmart SQL Interview Question:
Check out the Franklin Resources career page and see what type of rule best suits your qualifications.
SQL Question 2: Department Salaries
Suppose there was a table of Franklin Resources employee salaries, along with which department they belonged to. Write a query to compare the average salary of employees in each department to the company's average salary. Return the comparison result as 'higher', 'lower', or 'same' for each department. Display the department ID, payment month (in MM-YYYY format), and the comparison.
Code your solution to this interview question directly within the browser on DataLemur:
The solution is LONG – 30+ lines of SQL. You can find a detailed solution here: Department vs. Company Salary.
SQL Question 3: What's the difference between a unique and non-unique index?
Unique indexes help ensure that there are no duplicate key values in a table, maintaining data integrity. They enforce uniqueness whenever keys are added or changed within the index.
To define a unique index in PostgreSQL, you can use the following syntax:
To define a non-unique index in PostgreSQL, you can use the following syntax:
Non-unique indexes on the other hand, are used to improve query performance by maintaining a sorted order of frequently used data values, but they do not enforce constraints on the associated table.
SQL Question 4: Calculate Assets Under Management (AUM) Growth Month over Month
Assume that Franklin Resources wants to analyze the growth of assets under the management of their portfolio managers month over month. Each portfolio manager can manage multiple portfolios. Given the provided table and table, write a SQL query to calculate each manager's month over month AUM growth rate in percentage. If there is no AUM of the previous month for comparison, display null.
Example Input:
| portfolio_id | manager_id | date | AUM |
|---|---|---|---|
| 1 | 1 | 2022-01-01 | 1000000 |
| 2 | 1 | 2022-02-01 | 1100000 |
| 3 | 1 | 2022-03-01 | 1200000 |
| 4 | 2 | 2022-01-01 | 1500000 |
| 5 | 2 | 2022-02-01 | 1700000 |
Example Input:
| manager_id | name |
|---|---|
| 1 | Kim |
| 2 | Alex |
Example Output:
| manager_id | month | AUM_growth |
|---|---|---|
| 1 | 2022-02 | 10 |
| 1 | 2022-03 | 9.09 |
| 2 | 2022-02 | 13.33 |
Answer:
This query first groups the data by portfolio manager and month, and calculates the total AUM for each portfolio manager for each month. The function is then used to create a new column containing the previous month's AUM. The month-over-month growth rate is then calculated using these two columns. The results are finally sorted by portfolio manager and month.
To practice a similar window function interview problem which uses RANK() on DataLemur's free online SQL code editor, solve this Amazon SQL question asked in a BI Engineer interview:
SQL Question 5: When would you use the function?
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 Franklin Resources 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.
| sales_person | closed_deals |
|---|---|
| Jason Wright | 4 |
| Drew Jackson | NULL |
| Chris Ho | 2 |
| Adam Cohen | NULL |
| Samantha Perez | 3 |
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:
| sales_person | closed_deals |
|---|---|
| Jason Wright | 4 |
| Drew Jackson | 0 |
| Chris Ho | 2 |
| Adam Cohen | 0 |
| Samantha Perez | 3 |
SQL Question 6: Filter Customer Records using LIKE Keyword
Given the table, find all records of customers whose "first_name" starts with "Ben" and "email" ends with "@franklinresources.com". Assumptions made are that a customer's first name and email form part of the records stored, matching the string pattern is case-insensitive and, that there are no trailing or leading spaces in both the and fields.
Example Input:
| customer_id | first_name | last_name | signup_date | |
|---|---|---|---|---|
| 6171 | ben | clarkson | ben.clarkson@franklinresources.com | 01/08/2022 00:00:00 |
| 7802 | Ben | Smith | ben.smith@mail.com | 05/10/2022 00:00:00 |
| 5293 | Benjamin | Franklin | benjamin.franklin@franklinresources.com | 22/06/2022 00:00:00 |
| 6352 | Bernie | Ruth | bernie.ruth@franklinresources.com | 16/07/2022 00:00:00 |
| 4517 | Ben | Lewis | ben.lewis@franklinresources.com | 02/12/2021 00:00:00 |
Example Output:
| customer_id | first_name | last_name | signup_date | |
|---|---|---|---|---|
| 6171 | ben | clarkson | ben.clarkson@franklinresources.com | 01/08/2022 00:00:00 |
| 5293 | Benjamin | Franklin | benjamin.franklin@franklinresources.com | 22/06/2022 00:00:00 |
| 4517 | Ben | Lewis | ben.lewis@franklinresources.com | 02/12/2021 00:00:00 |
Answer:
Here, the keyword is used together with the wildcard to filter out customer records from Franklin Resources that meet the required conditions. The wildcard represents any number of characters and is used to handle character casing. There are two conditions, one checks whether the starts with 'ben' and the second condition checks whether the ends with '@franklinresources.com'. If both conditions are true for a record, the corresponding row is returned by the query.
SQL Question 7: How are left and right joins different from each other?
{#Question-7}
Both left and right joins in SQL allow you to combine data from different tables based on a shared key or set of keys. For a concrete example of the difference between these two join types, say you had sales data exported from Franklin Resources's Salesforce CRM stored in a PostgreSQL database, and had access to two tables: and .
: retrieves all rows from the left table (in this case, the sales table) and any matching rows from the right table (the table). If there is no match in the right table, NULL values will be returned for the right table's columns.
- : retrieves all rows from the right table (in this case, the customers table) and any matching rows from the left table (the sales table). If there is no match in the left table, NULL values will be returned for the left table's columns.
SQL Question 8: Calculate Standard Deviation of Employee Ages
Franklin Resources is analyzing the demographic spread of their employees. The company wants you to calculate the standard deviation of the employees' ages for each department. The ages are furthermore rounded to the nearest whole number.
Assume that we are provided with the following table:
Example Input:
| employee_id | department | age |
|---|---|---|
| 1001 | Marketing | 45 |
| 1002 | Marketing | 50 |
| 1003 | Sales | 30 |
| 1004 | Sales | 35 |
| 1005 | Sales | 40 |
| 1006 | HR | 60 |
| 1007 | HR | 65 |
Example Output:
| department | std_dev_age |
|---|---|
| Marketing | 2.5 |
| Sales | 2.89 |
| HR | 2.5 |
Answer:
In PostgreSQL, the query would be the following:
This PostgreSQL query groups the records by the column, then calculates the standard deviation of ages for each department with the aggregate function. These resulting values are rounded to two decimal places with the function. This will give the standard deviation of ages in each department, which tells the company how spread out the ages are in each department. A higher standard deviation would indicate a wider age diversity, and a smaller standard deviation would indicate ages are closer to the average age in that department.
To practice a very similar question try this interactive Google Median Google Search Frequency Question which is similar for uses aggregation and rounding or this Alibaba Compressed Mean Question which is similar for <Involves calculations on user data.
Franklin Resources SQL Interview Tips
The key to acing a Franklin Resources SQL interview is to practice, practice, and then practice some more!
In addition to solving the earlier Franklin Resources SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Microsoft, Google, and Facebook.
Each problem on DataLemur has multiple hints, detailed solutions and most importantly, there is an interactive coding environment so you can right online code up your SQL query answer and have it executed.
To prep for the Franklin Resources SQL interview it is also wise to solve SQL questions from other investment management and private equity companies like:
In case your SQL coding skills are weak, forget about going right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.
This tutorial covers SQL concepts such as aggregate window functions and ordering data – both of these pop up routinely during SQL interviews at Franklin Resources.
Franklink Templeton Investments Data Science Interview Tips
What Do Franklin Resources Data Science Interviews Cover?
Besides SQL interview questions, the other types of questions to prepare for the Franklin Resources Data Science Interview are:
- Statistics and Probability Questions
- Python or R Coding Questions
- Open-Ended Data Case Studies
- ML Interview Questions
- Behavioral Interview Questions
How To Prepare for Franklin Resources Data Science Interviews?
I'm a tad biased, but I believe the best way to study for Franklin Resources Data Science interviews is to read the book Ace the Data Science Interview.
The book covers 201 data interview questions taken from FAANG (FB, Apple, Amazon, Netflix, Google). It also has a crash course covering Product Analytics, SQL & ML. And finally it's helped a TON of people, which is how it's gotten to be an Amazon best-seller with over 1000+ 5-star reviews.