9 Fiserv SQL Interview Questions - Can You Solve Them?
At Fiserv, Microsoft SQL Server is used quite frequently for managing financial data in databases, and extracting insights for their small business index. That's why Fiserv often tests SQL questions during interviews for Data Science, Analytics, and & Data Engineering jobs.
So, if you're trying to prepare for the SQL Interview, here’s 9 Fiserv SQL interview questions – can you solve them?
9 Fiserv SQL Interview Questions
SQL Question 1: Transaction Analysis Using Window Functions
Your goal is to help Fiserv analyze its customers' transaction records to identify monthly transaction trends for the SpendTrend product. You will need to write a SQL query that calculates the sum and average transaction amounts for each customer on a monthly basis, then ranks the customers based on these amounts using window functions.
Data for the problem is represented in the table.
Example Input:
| transaction_id | customer_id | transaction_date | amount |
|---|---|---|---|
| 5513 | 1775 | 06/08/2022 00:00:00 | 1500.00 |
| 8991 | 6002 | 06/10/2022 00:00:00 | 3000.00 |
| 4334 | 6002 | 06/18/2022 00:00:00 | 5000.00 |
| 3222 | 1231 | 07/26/2022 00:00:00 | 4000.00 |
| 1112 | 6002 | 07/05/2022 00:00:00 | 2000.00 |
Example Output:
| month | customer_id | total_amount | average_amount | rank |
|---|---|---|---|---|
| 6 | 6002 | 8000.00 | 4000.00 | 1 |
| 6 | 1775 | 1500.00 | 1500.00 | 2 |
| 7 | 6002 | 2000.00 | 2000.00 | 1 |
| 7 | 1231 | 4000.00 | 4000.00 | 2 |
Answer:
Here's the PostgreSQL query for the task:
This query first extracts the month from each transaction date and groups transactions by month and customer. It then calculates the total and average transaction amounts for each group in subquery .
In the main query, it uses a window function to generate the ranking of customers within each month based on the descending order of their total and average transaction amounts. This way, the customer with the highest total and average transaction amount in each month gets the top rank. The results are finally sorted by month and rank.
For more window function practice, try this Uber SQL problem within DataLemur's online SQL coding environment:
SQL Question 2: Transaction Frequency Analysis
As a Data Engineer at Fiserv, you are tasked with designing a database schema to track customer transactions made at various businesses. Each transaction record should include transaction id, customer id, business id, transaction date and amount spent. The business wants to identify top 5 customers who have made the most transactions in a given month.
Tables for this design could include:
To solve the given problem, write a PostgreSQL query.
Answer:
This query will return a table with columns for month, customer_id, and the total number of transactions made by that customer for that month. We're limiting the results to the top 5 customers based on transaction count. undefined
SQL Question 3: What does it mean for a DBMS to enforce atomicity, consistency, isolation, and durability?
ACID refers to the four key properties that are essential to the reliable and correct execution of database transactions. These properties are:
Atomicity: ensures that a transaction is treated as a single operation, and either all of the changes are made or none of them are! Basically, the database version of a "-FULL SEND-"
Consistency: ensures that the data is in a consistent state before and after a transaction is completed. For example, if wiring money to a friendly Nigerian prince whose fallen on hard times, consistency ensures that the total value of funds lost in my account is the same amount that's gained in the prince's account!
Isolation: ensures that the intermediate state of a transaction is invisible to other transactions. Back to the wiring-the-prince-some-money example, isolation ensures that another transaction sees the transferred funds in my account OR the princes, but not in both accounts at the same time
Durability: ensures that once a transaction has been completed successfully, the changes made by the transaction are permanent and cannot be undone, even in the event of a system failure. Basically, no taksies backsies (even if your system has a meltdown!).
SQL Question 4: Filter Customers Based on Financial Accounts Status
Fiserv is heavily involved in providing integrated technology solutions to financial institutions. Assuming that Fiserv has a customer database and an associated financial accounts database, construct a SQL query that can filter customers based on whether they have outstanding loans or not, and if they have any, whether their account balance is above or below a certain threshold.
Example Input:
| customer_id | name | account_id |
|---|---|---|
| 123 | John Doe | 1001 |
| 789 | Jane Smith | 1002 |
| 456 | Amy Brown | 1003 |
Example Input:
| account_id | loan_status | account_balance |
|---|---|---|
| 1001 | No outstanding loan | 1500 |
| 1002 | Has outstanding loan | 10000 |
| 1003 | No outstanding loan | 500 |
The task is to return customer names and account balance for customers who have no outstanding loans and their account balance is above $1000.
Answer:
This query joins both tables on the account_id, then filters rows based on the conditions provided in the WHERE clause. The selected column names of the final output are 'name' and 'account_balance'. undefined
SQL Question 5: When would you use the constraint?
A is a field in a table that references the of another table. It creates a link between the two tables and ensures that the data in the field is valid.
Say for example you had sales analytics data from Fiserv's CRM (customer-relationship management) tool.
The FOREIGN KEY constraint ensures that the data in the field of the "opportunities" table is valid, and prevents the insertion of rows in the table that do not have corresponding entries in the table. It also helps to enforce the relationship between the two tables and can be used to ensure that data is not deleted from the accounts table if there are still references to it in the opportunities table.
SQL Question 6: Calculate the Click-Through-Rate
At Fiserv, our digital product portfolio prompts users to make multiple decisions - viewing a product, adding it to the cart, and finally buying the product.
Assuming you are provided with two separate tables "products_views" (contains information on occasions a product was viewed by customers) and "products_added" (contains information on occasions a product was added to the cart by customers), can you write a SQL query to calculate the click-through-rate (CTR) from viewing a product to adding it to the cart? Let's define CTR as (number of products added to cart / number of products viewed) * 100%.
Example Input
| view_id | user_id | view_time | product_id |
|---|---|---|---|
| 101 | 1 | 06/08/2022 00:00:00 | 50001 |
| 102 | 2 | 06/10/2022 00:00:00 | 69852 |
| 103 | 3 | 06/18/2022 00:00:00 | 50001 |
| 104 | 4 | 07/26/2022 00:00:00 | 69852 |
| 105 | 5 | 07/05/2022 00:00:00 | 69852 |
Example Input
| add_id | user_id | add_time | product_id |
|---|---|---|---|
| 201 | 1 | 06/08/2022 00:05:00 | 50001 |
| 202 | 2 | 06/10/2022 00:15:00 | 69852 |
| 203 | 3 | 06/18/2022 00:10:00 | 50001 |
| 204 | 5 | 07/05/2022 00:10:00 | 69852 |
Answer
In the above query, we join the "products_views" and "products_added" tables on "product_id" and "user_id". We then group the result by "product_id" and calculate the CTR for each product by taking the count of product_ids in "products_added" and dividing it by the count of product_ids in "products_views". Lastly, we order by CTR to see the product with highest CTR at the top.
To solve a related SQL interview question on DataLemur's free online SQL coding environment, attempt this Facebook SQL Interview question:
SQL Question 7: What does database normalization mean?
To normalize a database, tables are divided into smaller, more specialized ones and relationships between them are defined via primary and foreign keys. This minimizes redundancy, making the database more flexible, scalable, and easier to maintain. Normalization also helps to ensure the accuracy of the data by reducing the likelihood of inconsistencies and errors.
SQL Question 8: Analyzing Customers' Transactions in Fiserv
You are a data analyst at Fiserv, a global provider of financial services technology. One of your main duties is to analyze the client transactions and form actionable insights from it. Your company has two main tables - and
The table holds information about all the clients, while the table contains all transactions done by these customers. The data schema for these tables is as follows:
Example Input:
| customer_id | first_name | last_name | email_id |
|---|---|---|---|
| 101 | John | Doe | john.doe@example.com |
| 102 | Jane | Smith | jane.smith@example.com |
| 103 | Luke | Brown | luke.brown@example.com |
| 104 | Liam | Anderson | liam.anderson@example.com |
Example Input:
| transaction_id | customer_id | transaction_date | amount |
|---|---|---|---|
| 2001 | 101 | 2020-02-15 | 500.00 |
| 2002 | 102 | 2020-03-02 | 450.00 |
| 2003 | 102 | 2020-04-05 | 100.00 |
| 2004 | 103 | 2020-04-07 | 1100.00 |
| 2005 | 104 | 2020-04-05 | 2000.00 |
Write a SQL query to join these two tables and retrieve customer's name, email, and total transaction amount for each customer for the month of April, 2020 and order the result by descending order of the total transaction amount.
Answer:
This query joins the customers and transactions table on . It then filters the transactions made in April 2020. The use of and does the filtering. This query then groups transactions by customers and calculates the total transaction amount made by each customer. The resulting data set is ordered in decreasing order of total transaction amount.
Because joins come up frequently during SQL interviews, try an interactive Spotify JOIN SQL question:
SQL Question 9: Calculate Monthly Average Transaction Amount
Fiserv, as a global leader in payments and financial services technology solutions, handles countless transactions daily. Assume you are a data analyst at Fiserv, and you've been asked to write a SQL query that would calculate the average transaction amount for each month from the "transactions" table.
Example Input:
| transaction_id | account_id | transaction_date | amount |
|---|---|---|---|
| 22031 | 970205 | 2022-05-10 10:15:00 | 35.50 |
| 18759 | 1089010 | 2022-06-08 07:25:00 | 830.25 |
| 30891 | 301250 | 2022-06-21 16:30:00 | 485.00 |
| 13247 | 972234 | 2022-07-18 11:20:00 | 120.75 |
| 29083 | 1089010 | 2022-07-30 12:45:00 | 645.00 |
To solve this problem, you would have to extract the month from the transaction_date and group by this extracted month. Your output should display the month and the corresponding average transaction amount.
Example Output:
| month | average_amount |
|---|---|
| 5 | 35.50 |
| 6 | 657.63 |
| 7 | 382.88 |
Answer:
The above query starts by extracting the month from the transaction_date column in the transactions table. This is achieved with the command. Then, we calculate the average amount for each month using the function. Finally, the obtained results are grouped by month and sorted in ascending order. This will produce a table that shows the average transaction amount for each month. undefined
Fiserv SQL Interview Tips
The best way to prepare for a Fiserv SQL interview is to practice, practice, practice.
Besides solving the earlier Fiserv SQL interview questions, you should also solve the 200+ tricky sql questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon.
Each problem on DataLemur has hints to guide you, detailed solutions and best of all, there's an interactive coding environment so you can right online code up your query and have it checked.
To prep for the Fiserv SQL interview you can also be a great idea to practice SQL questions from other fintech companies like:
But if your SQL coding skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this free SQL tutorial.
This tutorial covers things like handling timestamps and UNION – both of which come up frequently during Fiserv interviews.
Fiserv Data Science Interview Tips
What Do Fiserv Data Science Interviews Cover?
For the Fiserv Data Science Interview, besides SQL questions, the other types of questions to prepare for are:
- Probability & Stats Questions
- Python or R Programming Questions
- Data Case Study Questions
- Machine Learning Questions
- Behavioral & Resume-Based Questions
How To Prepare for Fiserv Data Science Interviews?
To prepare for Fiserv Data Science interviews read the book Ace the Data Science Interview because it's got:
- 201 interview questions taken from Facebook, Google & startups
- a refresher covering SQL, AB Testing & ML
- over 900+ reviews on Amazon & 4.5-star rating