11 Ally Financial SQL Interview Questions (Updated 2024)
Ally Financial employees use SQL for analyzing complex financial data for decision-making processes, and automating data pipelines to enhance business operations. Because of this, Ally Financial covers SQL query questions during interviews for Data Analytics, Data Science, and Data Engineering jobs.
Thus, to help you practice, we've curated 11 Ally Financial SQL interview questions – can you solve them?
11 Ally Financial SQL Interview Questions
SQL Question 1: Identify the VIP Customers
Ally Financial has a number of services related to banking and finance. One of their critical operations are the transactions made by the clients. For clarity in this exercise, let's assume that you have access to the "Transactions" table. Each row in the table represents an unique financial transaction by each customer. The table has the following schema:
| transaction_id | user_id | amount | transaction_type | transaction_date |
|---|---|---|---|---|
| 1001 | 567 | 5000 | deposit | 2022-05-01 |
| 1002 | 101 | 10000 | withdrawal | 2022-06-01 |
| 1003 | 567 | 15000 | deposit | 2022-07-01 |
| 1004 | 789 | 20000 | withdrawal | 2022-07-01 |
| 1005 | 101 | 5000 | deposit | 2022-08-01 |
Here, "transaction_id" is a unique identifier for every transaction, "user_id" is the identifier for the customer, "amount" is the dollar amount of the transaction, "transaction_type" is the type of transaction, and "transaction_date" is the date of the transaction.
Your task is to write a SQL query to identify the VIP customers in the second quarter of 2022. A VIP customer is defined as a user who had made total deposits of at least $10,000 during that quarter.
Answer:
The above query selects the user_id and total deposits made by each user from the transactions table for the second quarter of 2022. Users are considered VIP if their total deposits are at least $10,000. This is ensured by the HAVING clause in the SQL statement.
To practice a related customer analytics question on DataLemur's free online SQL code editor, try this Microsoft Azure Cloud SQL Interview Question:
SQL Question 2: Department Salaries
Imagine there was a table of Ally Financial employee salary data, 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.
Try this question and run your code right in DataLemur's online SQL environment:
The solution is LONG – 30+ lines of SQL. You can find a step-by-step solution with hints here: Department Salaries.
SQL Question 3: What's database denormalization?
Database denormalization is when you add redundancy to a database, and break typical normalization rules (codified by the 1st, 2nd, 3rd normal forms).
Denormalization is typically used to improve the performance of a database, particularly when the database is being for OLAP (Online Analytical Processing) purposes. By denormalizing a database, you can reduce the number of joins that are required to retrieve data, which can greatly improve the speed of queries since joins are costly and slow. However, denormalization can also introduce some problems, such as increased data redundancy and the need for more complex update and delete operations since data has been duplicated into multiple tables.
In general, denormalization should be used with caution and only after careful consideration of the trade-offs involved. It's typically better to start with a well-normalized database design then denormalize only if your database isn't scaling as well as you want.
SQL Question 4: Calculate Average Monthly Interest Amount per Account
As an analyst for Ally Financial, you are asked to analyze the realtime transaction data of customer accounts and derive meaningful insights. Assume you have a dataset containing the interest transactions for each of the customer accounts. For the task at hand, you're required to write a SQL query that calculates the average monthly interest amount per account.
Example Input:
| transaction_id | account_id | transaction_date | transaction_type | amount |
|---|---|---|---|---|
| 1 | 123 | 01/05/2022 | Interest | 5.00 |
| 2 | 123 | 01/25/2022 | Interest | 6.00 |
| 3 | 456 | 01/10/2022 | Interest | 3.00 |
| 4 | 456 | 02/10/2022 | Interest | 4.00 |
| 5 | 123 | 02/05/2022 | Interest | 7.00 |
| 6 | 456 | 02/27/2022 | Interest | 6.00 |
Expected Output:
| month | account_id | avg_interest_amount |
|---|---|---|
| 1 | 123 | 5.50 |
| 1 | 456 | 3.00 |
| 2 | 123 | 7.00 |
| 2 | 456 | 5.00 |
Answer:
This query calculates the average of "Interest" transactions per each month. The function extracts the month from the . The function is being used as an aggregate function to calculate the average interest amount and its behavior is modified by the clause, which associates it with a defined by the clause. Therefore it computes the average for each partition (i.e., for each combination of and month).
p.s. Window functions show up super often during SQL interviews, so practice the 27+ window function questions on DataLemur
SQL Question 5: How are left and right joins different from each other?
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A join in SQL allows you to retrieve data from multiple tables and combine it into a single set of results.
To demonstrate the difference between left vs. right join, 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 sales table, which has data on how many products were sold and which Google Ads keyword drove that sale.
: A LEFT JOIN retrieves all rows from the left table (in this case, the table) and any matching rows from the right table (the Sales table). If there is no match in the right table, values will be returned for the right table's columns.
: A RIGHT JOIN retrieves all rows from the right table (in this case, the Sales table) and any matching rows from the left table (the table). If there is no match in the left table, values will be returned for the left table's columns.
SQL Question 6: Ally Financial Bank Branch Performance Analysis
Ally Financial is a digital financial services company that includes banking operations, retirement and investing services, and car loans. The company would like to assess the performance of their bank branches over the last month. Specifically, they want to know the total number of transactions, the total value of deposits, and the total value of withdrawals at each of their bank branches. Assume you have 2 tables: and .
Example Input
| branch_id | branch_name | branch_city |
|---|---|---|
| 101 | Ally Detroit | Detroit |
| 102 | Ally San Francisco | San Francisco |
| 103 | Ally New York | New York |
| 104 | Ally Boston | Boston |
| 105 | Ally Chicago | Chicago |
Example Input
| transaction_id | branch_id | account_id | transaction_type | transaction_value | transaction_date |
|---|---|---|---|---|---|
| 5001 | 101 | 40001 | Deposit | 15000 | 10-01-2022 |
| 5002 | 102 | 40012 | Withdraw | 5000 | 10-02-2022 |
| 5003 | 101 | 40004 | Deposit | 10000 | 10-03-2022 |
| 5004 | 103 | 40011 | Deposit | 25000 | 10-04-2022 |
| 5005 | 104 | 40015 | Withdraw | 4000 | 10-05-2022 |
Answer:
In the above query, we're joining the table with the table on . For each branch, we count the number of transactions (total_transactions), sum the value of deposits (total_deposits), and sum the value of withdrawals (total_withdrawals). We filter to only consider transactions from the last month using . The data is grouped by and sorted in descending order by the total number of transactions.
SQL Question 7: What's a cross-join, and why are they used?
A cross-join, also known as a cartesian join, is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. This results in a table with a row for every possible combination of rows from the two input tables.
An example of when this might be useful is if you wanted to first make a dataset containing all possible pairs of customers and products data, in order to later build a Machine Learning model to predict the probability of a customer purchasing a particular product.
However, it is important to note that cross-joins can create very large tables, especially if the input tables have a large number of rows. For example, if you had 10,000 customers and 5,000 different product SKUs, the resulting cross-join would have 50 million rows.
SQL Question 8: Calculate the Click-through Conversion Rate for Ally Financial
As a data analyst at Ally Financial, you are tasked with analyzing the efficiency of a new advertising campaign. Your job is to calculate the click-through conversion rate. The click-through conversion rate is defined as the number of users who clicked on an ad and subsequently added a product from the ad to their cart (), divided by the total number of clicks on that ad ().
Example Input:
| click_id | ad_id | user_id | click_time |
|---|---|---|---|
| 001 | 100 | 1234 | 2022-08-01 13:00:00 |
| 002 | 100 | 7890 | 2022-08-01 13:05:00 |
| 003 | 100 | 4567 | 2022-08-01 13:10:00 |
| 004 | 200 | 1234 | 2022-08-01 13:15:00 |
| 005 | 200 | 7890 | 2022-08-01 13:20:00 |
Example Input:
| addition_id | ad_id | user_id | addition_time |
|---|---|---|---|
| A01 | 100 | 1234 | 2022-08-01 13:02:00 |
| A02 | 100 | 7890 | 2022-08-01 13:07:00 |
| A03 | 200 | 1234 | 2022-08-01 13:18:00 |
Answer:
In the above PostgreSQL script, a left join is used to combine the and tables on both and . Then, conversion rates are calculated for each ad by dividing by for each . The conversion rates give a ratio of how many users that clicked on an ad also added a product to their cart, helping to assess the success of the new advertising campaign.
To solve a related SQL problem on DataLemur's free online SQL code editor, solve this Facebook SQL Interview question:
Check out the most recent annual reports and proxy statements from Ally Financial and see how they have performed over the years.
SQL Question 9: Calculate Average Loan Amount by Loan Type
As a data analyst at Ally Financial, one of your tasks is to analyze lending patterns among customers. Specifically, your manager wants to know the average loan amount accepted by customers for each loan type in the last quarter. Write a SQL query that can provide this information.
Here is your dataset, including Loan ID, Customer ID, Loan Type, Loan Amount, and Accepted Date:
Example Input:
| loan_id | customer_id | loan_type | loan_amount | accepted_date |
|---|---|---|---|---|
| 1001 | 12 | Personal | 25000 | 01/10/2022 |
| 1002 | 32 | Auto | 18000 | 01/15/2022 |
| 1003 | 45 | Auto | 22000 | 02/12/2022 |
| 1004 | 12 | Personal | 20000 | 02/19/2022 |
| 1005 | 45 | Mortgage | 150000 | 03/25/2022 |
Your task is to return a summary table that includes the loan type and the average loan amount for the last quarter.
Example Output:
| loan_type | avg_loan_amount |
|---|---|
| Personal | 22500.00 |
| Auto | 20000.00 |
| Mortgage | 150000.00 |
Answer:
This SQL query calculates the average loan amount for each type of loan that was accepted in the last quarter. It selects the 'loan_type' and the average of 'loan_amount' from the 'loans' table, for records where the 'accepted_date' falls within the last quarter. The results are then grouped by 'loan_type', producing the average loan amount for each type of loan.
SQL Question 10: In SQL, are values same the same as zero or a blank space?
A NULL value represents a missing or unknown value. It is different from a zero or a blank space, which are actual values. It is important to handle NULL values properly in SQL because they can cause unexpected results if not treated correctly.
SQL Question 11: Find Customers in a Specific Location
As an analyst at Ally Financial, you are tasked with the job of tracking the number of customers in specific areas. In the customer database, the column stores the customer's residential address in the form: "Number, Street, City, State, PostalCode". We are interested in customers who reside in Michigan state (abbreviated as MI).
Given the table in the customer records database, write an SQL query that retrieves the , and of customers who reside in Michigan (MI).
For example, if the table was:
Example Input:
| customer_id | name | address |
|---|---|---|
| 101 | John Doe | 1234 Park St, Detroit, MI, 45730 |
| 102 | Jane Smith | 5678 Broadway, Houston, TX, 44123 |
| 103 | Richard Miller | 91011 State ave, Grand Rapids, MI, 49506 |
| 104 | Emma Johnson | 1213 Hill road, Los Angeles, CA, 90210 |
| 105 | Oliver Brown | 1415 Pine St, Ann Arbor, MI, 48103 |
You should return:
Example Output:
| customer_id | name | address |
|---|---|---|
| 101 | John Doe | 1234 Park St, Detroit, MI, 45730 |
| 103 | Richard Miller | 91011 State ave, Grand Rapids, MI, 49506 |
| 105 | Oliver Brown | 1415 Pine St, Ann Arbor, MI, 48103 |
Answer:
This PostgreSQL query uses the clause to filter out the records of customers who do not reside in Michigan (MI). Inside the clause, the '%' character is used as a wildcard to match any sequence of characters. Thus, '%, MI, %' matches any string that has ', MI, ' anywhere within it. In the context of this problem, ', MI, ' will appear in the string if, and only if, the customer resides in Michigan.
Preparing For The Ally Financial SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Ally Financial SQL interview is to solve as many practice SQL interview questions as you can!
Beyond just solving the earlier Ally Financial SQL interview questions, you should also solve the 200+ tricky 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 crucially, there is an interactive coding environment so you can instantly run your SQL query answer and have it checked.
To prep for the Ally Financial SQL interview you can also be useful to practice interview questions from other banking & finanacial services companies like:
However, if your SQL foundations are weak, forget about diving straight into solving questions – go learn SQL with this SQL tutorial for Data Analytics.
This tutorial covers things like RANK() window functions and handling timestamps – both of these come up often in SQL job interviews at Ally Financial.
Ally Financial Data Science Interview Tips
What Do Ally Financial Data Science Interviews Cover?
In addition to SQL interview questions, the other topics to practice for the Ally Financial Data Science Interview include:
- Statistics and Probability Questions
- Python or R Programming Questions
- Product & Business Analytics Questions
- ML Modelling Questions
- Behavioral & Resume-Based Questions
How To Prepare for Ally Financial Data Science Interviews?
I'm sort of biased, but I think the best way to prepare for Ally Financial Data Science interviews is to read the book I wrote: Ace the Data Science Interview.
The book covers 201 interview questions taken from tech companies like Google & Microsoft. It also has a refresher covering SQL, Product-Sense & 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.