10 Alteryx SQL Interview Questions (Updated 2024)

At Alteryx, SQL is often used for querying and processing large datasets for analytics and structuring and managing the company's vast proprietary data assets. So, it shouldn't surprise you that Alteryx frequently asks SQL coding questions during interviews for Data Analyst, Data Science, and BI jobs.

Thus, to help you practice for the Alteryx SQL interview, we'll cover 10 Alteryx SQL interview questions – able to answer them all?

10 Alteryx SQL Interview Questions

SQL Question 1: Compute Average Product Rating by Month

A company, Alteryx, collects product reviews from its users and stores them in a SQL database. You have been given data in a table named where each row represents a single review submitted by a user for a specific product on the website. The table contains the following columns:

• : Unique identifier for the review.
• : Unique identifier for the user.
• : Date and time the review was submitted.
• : Unique identifier for the product.
• : The star rating given by the user in the review (1-5 stars).

Your task is to write a SQL query using window functions that calculates the monthly average star rating for each product.

Example Input:

Answer:

This SQL query uses a window function to calculate the average rating for each product for each month. It partitions the data by product_id and the month of submit_date and then applies the average function to the 'stars' column. The clause then groups the result by product_id and month to produce a single row for each combination.

Example Output:

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

SQL Question 2: Sales Tracking of Alteryx Products.

As Alteryx Inc., a company developing data analytics and visualization tools, we have a number of products in our portfolio. We have been tracking the sales of these products across different countries. We are interested in understanding the top 3 best selling products in each country.

For the purpose of this question, consider the following tables.

Example Input:

Example Input:

The task is to write a PostgreSQL query to find out each country's top 3 best-selling products based on the number of units sold.

Answer:

An SQL query that might solve the problem is:

This query first aggregates the total units sold for each product in each country. Then it ranks the products within each country based on the total units sold. Finally, it retrieves the top 3 products of each country and their corresponding total units sold.

SQL Question 3: What does it mean to use a UNIQUE constraint in a database?

The UNIQUE constraint makes sure that all values in a column are distinct. It is often paired with other constraints, like NOT NULL, to ensure that the data follows certain rules.

For example, say you were an analyst on the marketing team at Alteryx, and had access to a database on marketing campaigns:

In this example, the UNIQUE constraint is applied to the "campaign_name" field to ensure that each campaign has a unique name. This helps to ensure the integrity of the data in the table and prevents errors that could occur if two campaigns had the same name.

SQL Question 4: Filter Customers in Alteryx

Imagine you are a data analyst working for Alteryx, a company that provides subscription-based services to its clients. You have been given a task to investigate the database of customers for a certain period. Your task is to filter out the data of customers who subscribed after 01/01/2021, are still active, and whose subscription cost is over $50.

Example Input:

Answer:

This SQL query is filtering customer records to find those who subscribed after January 1, 2021, who are still actively subscribed, and who pay more than $50 for their subscription. The query starts with which returns all columns. The specifies the table. The clause combines three boolean conditions with , which means that all the conditions need to be true simultaneously for any record to be included in the output.

SQL Question 5: What's denormalization, and when does it make sense to do it?

Imagine you've got giant AF jigsaw puzzle with thousands of pieces, and each piece represents a piece of data in your database. You've spent hours organizing the puzzle into neat little piles, with each pile representing a table in your database. This process is called normalization, and it's a great way to make your database efficient, flexible, and easy to maintain.

But what if you want to solve the puzzle faster (aka make your queries run faster?)?

That's where denormalization comes in – Denormalization is like the puzzle-solving equivalent of taking a shortcut!

Instead of putting all the pieces in separate piles, you might decide to clone some of the pieces, and then have that one puzzle piece be put into multiple piles. Clearly, we are breaking the rules of physics, but that's just like de-normalization because it breaks the normal rules of normalization (1st, 2nd, 3rd normal forms).

By adding redundant puzzle pieces, it can be easier to find the pieces you need, but it also means that you have to be extra careful when you're moving pieces around or adding new ones (aka INSERT/UPDATE commands become more complex).

On the plus side, denormalization can improve the performance of your database and make it easier to use. On the downside, it can make your database more prone to errors and inconsistencies, and it can be harder to update and maintain. In short, denormalization can be a helpful tool, but it's important to use it wisely!

SQL Question 6: Click Through Rate Analysis for Alteryx

You are a data analyst at Alteryx and your marketing team runs a number of online ad campaigns. They want to evaluate the effectiveness of their campaigns by calculating click-through conversion rates, which is the percentage of users who clicked the ad and then later added a product to the cart.

Given two tables:

1. table captures every click on an ad.

   Example Input:

   click_id	user_id	ad_id	timestamp
   4012	1101	485	2019-07-24 13:20:43
   3417	1325	755	2019-07-24 13:42:07
   8035	1101	485	2019-07-25 14:20:33
   7524	1572	866	2019-07-26 15:14:19
   6213	1781	755	2019-07-27 16:12:37

2. table captures every time a product is added to the cart.

   Example Input:

   addition_id	user_id	product_id	timestamp
   7151	1101	666	2019-07-24 14:20:33
   7303	1101	444	2019-07-26 16:42:39
   6084	1572	555	2019-07-27 17:12:48
   7914	1781	666	2019-07-28 18:13:58
   6282	1325	444	2019-07-28 19:14:07

Your task is to write a SQL query that calculates the click-through conversion rates for each ad.

Answer:

This query first calculates the number of unique clicks per ad and the number of unique additions per user. It then joins these two tables on and calculates the conversion rate by dividing additions by clicks. The function is used to handle cases where an ad was clicked but no product was added to the cart by that user.

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

SQL Question 7: What sets a cross join apart from a 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, Alteryx employees and Alteryx managers:

This natural join returns all rows from Alteryx 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 8: Filter Customer Records with Specific Pattern

Alteryx is a company that specializes in self-service data analytics. They have a database of customer records with information such as Customer ID, Name, Country and Email Address. As part of their marketing efforts, they want to target their customers based in the United States and have a Gmail email address.

Write a SQL query to filter the customer database to find the customers that match these two conditions - they should be based in the United States and their email address should be a Gmail account.

Example Input:

Example Output:

Answer:

This PostgreSQL query filters out the records in the customer_records table and only returns the records for customers who are based in the United States and their email address contains '@gmail.com', indicating they are Gmail users. The 'LIKE' keyword is used to match patterns in SQL and the '%' sign is a wildcard that matches any sequence of characters. Therefore, '%@gmail.com' matches any email address that ends with '@gmail.com'.

SQL Question 9: Calculate Performance Score

You are provided with a database containing sales information of Alteryx Company several employees. Each row represents a sale done by an employee. The performance score for an employee is calculated as follows:

• Take the absolute difference between the total sales of this month and the same month of the previous year.
• Round this value up to the nearest integer.
• If the difference is positive, add a 20% bonus. If it's negative, subtract a 20% penalty.
• The result should never drop below zero.
• Finally, calculate the square root of this final value and keep the result up to 2 decimal places.

Write a SQL query to calculate the sales performance score for each salesperson for each month of year 2022.

Example Input:

Answer:

In this solution, we first calculate the monthly sales for each salesperson for each year. This is done in the CTE. Next, we calculate the performance score for 2022 by joining the sales of 2022 and 2021 on salesperson_id and month and calculating the score, which is done in the CTE. In the final SQL, we calculate the square root of score (making sure it's zero if it's negative) and output it as the performance score of each salesperson for each month in year 2022.

To practice a very similar question try this interactive Wayfair Y-on-Y Growth Rate Question which is similar for calculating growth rate based on previous data or this Amazon Average Review Ratings Question which is similar for calculating averages on a specific metric.

SQL Question 10: How is the constraint used in a database?

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.

For example, if you have a table of Alteryx customers and an orders table, the customer_id column in the orders table could be a that references the id column (which is the primary key) in the Alteryx customers table.

The constraint helps maintain the integrity of the data in the database by preventing the insertion of rows in the table that do not have corresponding entries in the table. It also enforces the relationship between the two tables and prevents data from being deleted from the table if it is still being referenced in the table.

How To Prepare for the Alteryx SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Alteryx SQL interview is to solve as many practice SQL interview questions as you can! Beyond just solving the above Alteryx SQL interview questions, you should also solve the 200+ FAANG SQL Questions on DataLemur which come from companies like Microsoft, Google, and Facebook.

Each DataLemur SQL question has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there's an interactive coding environment so you can right in the browser run your SQL query and have it graded.

To prep for the Alteryx SQL interview you can also be useful to solve interview questions from other tech companies like:

• Databricks SQL questions

• Bayanat AI SQL questions

• Snowflake SQL questions

• Informatica SQL questions

In case your SQL coding skills are weak, don't worry about diving straight into solving questions – go learn SQL with this SQL interview tutorial.

This tutorial covers things like sorting results with ORDER BY and CASE/WHEN statements – both of these show up often in Alteryx SQL interviews.

Alteryx Data Science Interview Tips

What Do Alteryx Data Science Interviews Cover?

In addition to SQL interview questions, the other types of problems covered in the Alteryx Data Science Interview are:

• Statistics Interview Questions
• Python Pandas or R Coding Questions
• Product Analytics Questions
• ML Interview Questions
• Behavioral & Resume-Based Questions

How To Prepare for Alteryx Data Science Interviews?

The best way to prepare for Alteryx Data Science interviews is by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from companies like Microsoft, Google & Amazon
• A Refresher on SQL, Product-Sense & ML
• Great Reviews (900+ reviews, 4.5-star rating)