11 Vertex SQL Interview Questions (Updated 2024)

Updated on

March 2, 2024

At Vertex, SQL is often used for extracting and analyzing pharmaceutical research and development data, and for managing patient and medical trial databases. So, it shouldn't surprise you that Vertex almost always asks SQL problems during interviews for Data Science and Data Engineering positions.

To help you ace the Vertex SQL interview, we'll cover 11 Vertex SQL interview questions – how many can you solve?

11 Vertex SQL Interview Questions

SQL Question 1: Compute Ranking of Sales Representatives Based on Total Sales

A Vertex representative needs to evaluate the performance of their sales team for every quarter of 2021. They have a database with two tables: and . The table has details about all sales representatives like their and . The table has details of the sales for the year with , , and .

Calculate the ranking of sales representatives for every quarter based on their total sales. The ranking should be in descending order, so #1 indicates the representative with highest sales.

rep_idrep_name
1John
2Robert
3Anna
4Roger
5Sophie
Example Input:
rep_idsale_datesale_amount
101/10/20212500
201/30/20213500
302/15/20213000
402/20/20212300
503/30/20214000
104/10/20212000
205/20/20213500
305/30/20214000
406/25/20213000
506/30/20214200
107/10/20212500
208/30/20215500
308/15/20216000
409/25/20215300
509/20/20214000
110/30/20216000
211/20/20215500
311/30/20215200
412/25/20216200
512/30/20217000

The query first groups records by quarter and calculates total sales for each representative in each quarter. Then it assigns ranks to each representative in each quarter based on their total sales using the function. The function is a window function that assigns a unique row number to each row depending upon the provided partition and order. The clause is used to create a separate window for each quarter, and the clause orders the sales inside these windows in descending order. When the sales are the same for multiple representatives, the function assigns the same rank to each and skips the next number(s). The result is then ordered by quarter and ranking.

To practice a related window function SQL problem on DataLemur's free interactive coding environment, try this Google SQL Interview Question:

SQL Question 2: Filter Vertex's Customer Records

Let's say Vertex is a company that produces different types of vehicles. The company maintains a customer records database with the following tables:

• A 'Customers' table, which stores unique customer IDs, their names, and the date they became a customer
• A 'Vehicles' table, which stores unique vehicle IDs, their make, model, and color
• An 'Orders' table, which logs each sale with an order number, the ID of the customer, the ID of the vehicle purchased, and the date of the purchase

Could you write a query that pulls a list of customers who became customers after January 1, 2021, and have purchased at least one red vehicle?

Example Input:
customer_idnamecustomer_since
001John Smith08/10/2020
002Jane Doe01/15/2021
003Tom Brown06/23/2021
Example Input:
vehicle_idmakemodelcolor
100FordMustangRed
101NissanAltimaBlue
102ToyotaCamryRed
Example Input:
order_numbercustomer_idvehicle_idorder_date
50100110109/15/2020
50200210202/10/2021
50300310007/01/2021

This query first joins the 'Customers', 'Orders' and 'Vehicles' tables on the respective customer ID and vehicle ID columns. The WHERE clause then filters this combined data for customers who became customers after January 1, 2021, and have purchased a red vehicle.

SQL Question 3: Can you explain what a cross-join is and the purpose of using them?

A cross-join, also known as a cartesian join, is a type of join that returns the cross-product of two tables. In a cross-join, each row from the first table is paired with every row from the second table, resulting in a new table that has a row for each possible combination of rows from the two input tables.

For example, say you worked on the Marketing Analytics team at Vertex, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).

Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:

You could this query to generate all possible combinations of ad copy and ad creative to help you create more effective ads for Vertex. Just be careful: if you had 1,000 rows of ad copy and 1,000 different image creatives, the resulting cross-join would have 1 million rows!

SQL Question 4: Finding the average salary of employees in each department

Given the and tables in the Vertex Company's database, write a SQL query to find the average salary of employees in each department.

Example Input:
employee_idfirst_namelast_namedepartment_idsalary
1JohnDoe100170000
2JaneSmith100280000
3JimBrown100175000
4JillJohnson100285000
5JakeDavis100172000
Example Input:
department_iddepartment_name
1001Finance
1002Marketing
Example Output:
department_nameavg_salary
Finance72333.33
Marketing82500

This query joins the and tables on the field. The clause then groups the result by , and for each group, the function calculates the average salary.

SQL Question 5: How do relational and non-relational databases differ?

While both types of databases are used to store data (no duh!), relational databases and non-relational (also known as NoSQL databases) differ in a few important ways:

Data model: Relational databases use a data model consisting of tables and rows, while NoSQL databases use a variety of data models, including document, key-value, columnar, and graph storage formats.

Data integrity: Relational databases use structured query language (SQL) and enforce strict data integrity rules through the use of foreign keys and transactions. NoSQL databases may not use SQL and may have more relaxed data integrity rules.

Structure: Relational databases store data in a fixed, structured format, while NoSQL databases allow for more flexibility in terms of data structure.

ACID compliance: Relational databases are typically into shrooms and are ACID-compliant (atomic, consistent, isolated, and durable), while NoSQL databases may not be fully ACID-compliant (but they try their best... and it's effort that counts...or at least that's what my gym teacher told me!)

SQL Question 6: Calculate the Click-Through-Rate

Vertex is interested in analyzing the click-through rates for their products. They track the times users view a product, click on the product and add that product to the cart.

Create a PostgreSQL query that calculates the click-through conversion rates from viewing a product to adding a product to the cart for each product.

Example Input:
view_iduser_idview_dateproduct_id
10011504/10/2022 00:00:0075001
20024004/12/2022 00:00:0072004
30032504/13/2022 00:00:0072004
40043804/14/2022 00:00:0075001
50051204/15/2022 00:00:0072004
Example Input:
60501504/10/2022 01:00:0075001
70502004/13/2022 02:00:0072004
80502504/13/2022 03:00:0072004

This query first joins views () and adds_to_cart () tables based on and . The ensures that all views are included even if there is no corresponding record in adds_to_cart. Then it groups data by and for each product calculates the click-through rate as the ratio of distinct users who added the product to the cart to distinct users who viewed the product.

Example Output:
product_idclick_through_rate
750010.50
720040.67

To solve a similar problem about calculating rates, try this TikTok SQL question within DataLemur's online SQL coding environment:

SQL Question 7: How do the 'BETWEEN' and 'IN' commands differ?

The and operators are both used to filter data based on certain criteria, but they work in different ways. is used to select values within a range, while is used to select values that match a list.

For instance, if you have a table called that contains the salary of each employee, along with which country they reside in, you could use the operator to find all employees who make between $130k and$160k:

To find all employees that reside in France and Germany, you could use the operator:

SQL Question 8: Calculate the total revenue for each product category

Vertex is a company that sells various products across multiple categories. Your task is to write a SQL query that calculates the total revenue for each product category for the month of August 2022.

Example Input:
sale_idproduct_idcategory_idsale_dateunits_soldsale_price
1001200108/05/202222100
1002201108/15/202214200
1003300208/18/202230150
1004301208/28/202242250
1005400308/10/202225300
Example Output:
category_idtotal_revenue
14600
212000
37500

The query selects the and calculates total revenue by multiplying with . The SUM function is used to get the total revenue for each category (). The WHERE clause filters to only include sales from the month of August in the year 2022. Finally, the query uses GROUP BY to group the data by , ensuring that the total revenue is calculated per product category.

SQL Question 9: Filter Vertex Customers by Email Domain

As an analyst at Vertex, you are tasked with understanding more about your customer's distribution across different email providers. You are particularly interested in customers using 'yahoo' as their email client. From the customer database, can you retrieve the records of all customers whose email ends with 'yahoo.com'?

Example Input:
customer_idfirst_namelast_nameemailcountry
324JohnDoejohn.doe@yahoo.comUSA
769SarahWilliamssarah.williams@yahoo.comUSA
1024BobMillerbob.miller@hotmail.comUK
2001AliceJohnsonalice.johnson@yahoo.comAustralia

This SQL script will retrieve all records in the 'vertex_customers' table where the 'email' column ends with 'yahoo.com'. The '%' symbol acts as a wildcard character, representing any number of characters preceding 'yahoo.com' in the email address.

SQL Question 10: Can you explain the distinction between cross join and natural join?

A cross join is a JOIN operation in SQL that creates a new table by pairing each row from the first table with every row from the second table. It is also referred to as a cartesian join. In contrast, a natural join combines rows from two or more tables based on their common columns, forming a new table. Natural joins are called "natural" because they rely on the natural relationship between the common columns in the joined tables.

Here's an example of a cross join:

Here's a natural join example using two tables, Vertex employees and Vertex managers:

This natural join returns all rows from Vertex employees where there is no matching row in managers based on the column.

One significant difference between cross joins and natural joins is that the former do not require common columns between the tables being joined, while the latter do. Another distinction is that cross joins can generate very large tables if the input tables have a large number of rows, while natural joins only produce a table with the number of rows equal to the number of matching rows in the input tables.

SQL Question 11: Sales and Tax Calculation

You are given a table that includes details about Vertex's product sales. Each record includes the , , , , and .

Your task is to write a query to find the total sales for each product in July 2022, rounding it to the nearest cent. Furthermore, apply a tax of 7.5% to each sale if the product_id is even.

Example Input:
sale_idproduct_idsale_datequantity_soldunit_price
321080007/02/2022 00:00:009$13.75 542145007/05/2022 00:00:003$23.25
123080007/10/2022 00:00:0011$13.75 458745007/19/2022 00:00:005$23.25
963442507/29/2022 00:00:004\$24.00

This SQL query first checks if the is even by using MOD(). If it is, it calculates the total sale amount including a 7.5% tax. If not, it calculates the total sale amount without any tax. It then sums up the sale amounts for each product sold in July 2022 using SUM() and rounds the result to the nearest cent using the ROUND() function. It finally groups the sales by using GROUP BY to give total sales for each product sold in that month.

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating total sales for products or this Google Odd and Even Measurements Question which is similar for handling odd and even product ids.

Vertex SQL Interview Tips

The key to acing a Vertex SQL interview is to practice, practice, and then practice some more! Beyond just solving the above Vertex SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like FAANG tech companies and tech startups.

Each SQL question has multiple hints, step-by-step solutions and most importantly, there's an online SQL code editor so you can right in the browser run your SQL query answer and have it graded.

To prep for the Vertex SQL interview it is also useful to practice interview questions from other tech companies like:

In case your SQL coding skills are weak, don't worry about going right into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers SQL topics like removing NULLs and 4 types of JOINS – both of which show up often in Vertex SQL interviews.

Vertex Data Science Interview Tips

What Do Vertex Data Science Interviews Cover?

In addition to SQL query questions, the other types of questions to practice for the Vertex Data Science Interview are:

• Probability & Statistics Questions
• Python or R Programming Questions
• Product Analytics Questions
• Machine Learning Questions
• Resume-Based Behavioral Questions

How To Prepare for Vertex Data Science Interviews?

To prepare for Vertex Data Science interviews read the book Ace the Data Science Interview because it's got:

• 201 interview questions taken from tech companies like Google & Microsoft
• a refresher covering Stats, SQL & ML
• over 900+ 5-star reviews on Amazon