8 Truist Financial SQL Interview Questions (Updated 2024)
Truist Financial employees use SQL often for analyzing transactional data for fraud detection and optimizing information flow to enhance customer service. For this reason Truist Financial asks SQL questions in interviews for Data Analyst, Data Science, and BI jobs.
Thus, to help prep you for the Truist Financial SQL interview, we'll cover 8 Truist Financial SQL interview questions in this article.
8 Truist Financial SQL Interview Questions
SQL Question 1: Analyze Monthly Loan Performance
Truist Financial offers different types of loans to their customers. They want to analyze the performance of their loan products on a monthly basis by identifying the average interest rates and the total loan amounts for each product. The loan department maintains a database that keeps track of each loan taken by a customer.
Example Input:
| loan_id | customer_id | loan_date | product_type | loan_amount | interest_rate |
|---|---|---|---|---|---|
| 1 | 100 | 2022-07-01 | Home loan | 500000 | 5.1 |
| 2 | 200 | 2022-06-15 | Automobile loan | 20000 | 7.2 |
| 3 | 300 | 2022-06-20 | Student loan | 30000 | 4.6 |
| 4 | 400 | 2022-07-10 | Home loan | 600000 | 4.8 |
| 5 | 100 | 2022-07-15 | Student loan | 20000 | 4.5 |
You need to write the SQL query that provides the average interest rate and the total loan amount for each type of loan product on a monthly basis.
Example output:
| month | product_type | average_interest_rate | total_loan_amount |
|---|---|---|---|
| 6 | Automobile loan | 7.2 | 20000 |
| 6 | Student loan | 4.6 | 30000 |
| 7 | Home loan | 4.95 | 1100000 |
| 7 | Student loan | 4.5 | 20000 |
Answer:
The above SQL code first extracts the month from the column and couples that with to partition the data. This grouping allows us to calculate the average interest rate and total loan amount for each loan product for every month. The result of the query is ordered first by month, then by product type.
To practice another window function question on DataLemur's free online SQL code editor, try this Amazon SQL question asked in a BI Engineer interview:
SQL Question 2: Employee Salaries Higher Than Their Manager
Suppose you had a table of Truist Financial employee salary data. Write a SQL query to find the employees who earn more than their direct manager.
Truist Financial 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.
You can solve this problem interactively 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 detailed solution with hints here: Well Paid Employees.
SQL Question 3: What sets relational and NoSQL databases apart?
A non-relational (NoSQL) database is any database that does not use the typical tabular format of rows and columns like in relational databases.
While knowing the four different types of NoSQL databases is beyond the scope of most Data Analyst & Data Science interviews, Data Engineers at Truist Financial should vaguely refresh these concepts:
- Document Databases – this database is designed for storing and querying retrieving document data (where each key is associated with a flexible document)
- Key-Value Stores – these databases uses keys where each key is associated with only one value in a collection (similar to a Python dictionary data structure!)
- Wide-Column Stores – this database uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row within the same table. Remember: "-With great flexibility comes great responsiblity-" – Batman if he was learning about NoSQL databases!
- Graph Stores – represents data in terms of the graph data structure, with nodes and edges between entities
SQL Question 4: Customer Transaction Analysis
Truist Financial conducts several thousands of transactions daily and they want to efficiently track, analyze and report these transactions. Specifically, they are interested in understanding the total transaction amounts by type of transaction and by each customer each day. Truist Financial would like you to design a model with multiple tables that can help answer this question.
Assuming you start with the following tables.
Example Input:
| transaction_id | account_id | transaction_date | transaction_type | transaction_amt |
|---|---|---|---|---|
| 1001 | 00201 | 2022-06-08 | Deposit | 500.0 |
| 1002 | 00311 | 2022-06-07 | Withdrawal | 200.0 |
| 1003 | 00201 | 2022-06-06 | Deposit | 400.0 |
| 1004 | 00162 | 2022-06-08 | Deposit | 600.0 |
| 1005 | 00311 | 2022-06-08 | Withdrawal | 300.0 |
Example Input:
| account_id | customer_id |
|---|---|
| 00201 | 003 |
| 00311 | 007 |
| 00162 | 003 |
Write a SQL query in PostgreSQL that will provide a daily transaction total for each type of transaction for each customer.
Answer:
This query joins the table with the table on to associate each transaction with a customer (). It then groups the data by , , and and calculates the sum of for each grouping, effectively yielding the total transaction amount per transaction type for each customer for each day. The results are then ordered by and for better readability.
SQL Question 5: How does the constraint function, and in what scenarios might it be useful?
The CHECK constraint is used to enforce rules on the data in a specific column. If a row is inserted or updated with data that does not follow the CHECK constraint's rule, the operation will fail.
For example, say you had a database that stores ad campaign data from Truist Financial's Google Analytics account.
Here's what some constraints could look like:
In this example, the constraint is used to ensure that the "budget" and "cost_per_click" fields have positive values. This helps to ensure that the data in the database is valid and makes sense in the context of ad campaigns.
You can also use the constraint to ensure that data meets other specific conditions. For example, you could use a constraint to ensure that the "start_date" is before the "end_date" for each ad campaign.
SQL Question 6: Average Account Balances Grouped By Account Type And State
As a database administrator at Truist Financial, you are tasked to analyze the average account balance in various account types across different states. This will help the company understand bank customers' behaviors in different states and develop the best strategies accordingly.
Assuming that the company has a table structured as follows:
Example Input:
We want to find out the average balance of each account type in each state.
The expected output should be something like this:
Example Output:
Answer:
The PostgreSQL query to solve the problem will look like this:
This query groups the table by the 'state' and 'account_type' columns, and for each group, it calculates the average balance using the AVG() function. The final result will contain rows with unique combinations of states and account types, along with the average account balance for each combination.
SQL Question 7: What's a foreign key?
A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.
For example, let's look at the Truist Financial sales database:
truist_financial_sales:
+------------+------------+------------+------------+ | order_id | product_id | customer_id| quantity | +------------+------------+------------+------------+ | 1 | 222 | 1 | 2 | | 2 | 333 | 1 | 1 | | 3 | 444 | 2 | 3 | | 4 | 555 | 3 | 1 | +------------+------------+------------+------------+
In this table, and could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.
Check out the Truist career page and see what ype of role would be the best fit for you!
SQL Question 8: Find Customers in Specific Locations
As a data analyst at Truist Financial, your task involves customer segmentation based on various factors. One such factor is the location of the customer. For a marketing campaign, you are supposed to find all customers who live in cities whose names start with 'San'. The relevant table here is the table, which has the following structure:
Example Input:
| customer_id | first_name | last_name | city | state | zip_code |
|---|---|---|---|---|---|
| 124589 | Smith | Johnson | San Francisco | CA | 94109 |
| 897321 | John | Miller | San Diego | CA | 92101 |
| 785392 | Brian | Garcia | Los Angeles | CA | 92025 |
| 245789 | Sara | Moore | Sandwich | MA | 02563 |
| 784512 | Lucy | Jackson | San Antonio | TX | 78205 |
The task at hand is to write a SQL query that finds customers living in cities that start with 'San'.
Answer:
Here is the SQL query to solve the problem:
This query uses the 'LIKE' keyword along with a pattern that uses the '%' wildcard. The '%' wildcard in a 'LIKE' clause in SQL represents any sequence of characters. So 'San%' represents any string that starts with 'San'.
This query will return all rows (i.e., all customers) from the table where the value begins with 'San'. This includes cities such as 'San Francisco', 'San Diego', 'Sandwich', and 'San Antonio', among others.
Truist Financial SQL Interview Tips
The best way to prepare for a Truist Financial SQL interview is to practice, practice, practice.
Beyond just solving the above Truist Financial SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Facebook, Google and unicorn tech startups.
Each problem on DataLemur has hints to guide you, full answers and best of all, there is an interactive coding environment so you can right online code up your query and have it checked.
To prep for the Truist Financial SQL interview you can also be wise to practice interview questions from other banking & finanacial services companies like:
In case your SQL foundations are weak, don't worry about diving straight into solving questions – improve your SQL foundations with this SQL tutorial for Data Scientists & Analysts.
This tutorial covers things like advantages of CTEs vs. subqueries and inner vs. outer JOIN – both of these pop up routinely during Truist Financial interviews.
Truist Financial Data Science Interview Tips
What Do Truist Financial Data Science Interviews Cover?
In addition to SQL query questions, the other types of questions tested in the Truist Financial Data Science Interview include:
- Statistics & AB Testing Questions
- Python or R Coding Questions
- Analytics and Product-Metrics Questions
- ML Interview Questions
- Behavioral & Resume-Based Questions
How To Prepare for Truist Financial Data Science Interviews?
To prepare for Truist Financial Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from FAANG & startups
- a refresher on SQL, Product-Sense & ML
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