8 Wayfair SQL Interview Questions (Updated 2024)
At Wayfair, SQL is used day-to-day for analyzing customer purchasing trends and managing vast product inventory databases. So, it shouldn't surprise you that Wayfair LOVES to ask SQL coding questions in interviews for Data Science and Data Engineering positions.
Thus, to help you study for the Wayfair SQL interview, this blog covers 8 Wayfair SQL interview questions – can you solve them?
8 Wayfair SQL Interview Questions
SQL Question 1: Y-on-Y Growth Rate
Assume you're given a table containing information about Wayfair user transactions for different products. Write a query to calculate the year-on-year growth rate for the total spend of each product, grouping the results by product ID.
The output should include the year in ascending order, product ID, current year's spend, previous year's spend and year-on-year growth percentage, rounded to 2 decimal places.
Table:
| Column Name | Type |
|---|---|
| transaction_id | integer |
| product_id | integer |
| spend | decimal |
| transaction_date | datetime |
Example Input:
| transaction_id | product_id | spend | transaction_date |
|---|---|---|---|
| 1341 | 123424 | 1500.60 | 12/31/2019 12:00:00 |
| 1423 | 123424 | 1000.20 | 12/31/2020 12:00:00 |
| 1623 | 123424 | 1246.44 | 12/31/2021 12:00:00 |
| 1322 | 123424 | 2145.32 | 12/31/2022 12:00:00 |
Example Output:
| year | product_id | curr_year_spend | prev_year_spend | yoy_rate |
|---|---|---|---|---|
| 2019 | 123424 | 1500.60 | NULL | NULL |
| 2020 | 123424 | 1000.20 | 1500.60 | -33.35 |
| 2021 | 123424 | 1246.44 | 1000.20 | 24.62 |
| 2022 | 123424 | 2145.32 | 1246.44 | 72.12 |
This is the same question as problem #32 in the SQL Chapter of Ace the Data Science Interview!
Answer:
Here's a way to write a SQL block to solve this problem:
To solve this question on DataLemur's free online SQL code editor, try this Wayfair SQL interview question:
SQL Question 2: Calculate Monthly Average Ratings for Each product
Wayfair, an American e-commerce company that sells furniture and home-goods, tracks product reviews submitted by users on its platform. Each review has the following details - an unique review id, the user_id of the user who submitted the review, the timestamp at which the review was submitted, the id of the product which the review is about, and the number of stars given by the user in the review (on a scale of 1 to 5).
Given a table , with the structure shown below, write an SQL query that calculates, for each product, the average number of stars given in the reviews submitted each month. The result should be ordered by month and then product_id.
Example Input:
| review_id | user_id | submit_date | product_id | stars |
|---|---|---|---|---|
| 6171 | 123 | 2011-06-08 | 50001 | 4 |
| 7802 | 265 | 2011-06-10 | 69852 | 4 |
| 5293 | 362 | 2011-06-18 | 50001 | 3 |
| 6352 | 192 | 2011-07-26 | 69852 | 3 |
| 4517 | 981 | 2011-07-05 | 69852 | 2 |
Example Output:
| mth | product | avg_stars |
|---|---|---|
| 6 | 50001 | 3.50 |
| 6 | 69852 | 4.00 |
| 7 | 69852 | 2.50 |
Answer:
The above SQL query calculates the average stars of each product for each month by using the function and groups the output by month and product id. It orders the result by month and product so that it's easier to interpret. Please note that SQL function is a PostgreSQL function, and may not work in other SQL variations.
Pro Tip: Window functions are a frequent SQL interview topic, so practice all the window function problems on DataLemur
SQL Question 3: How would you improve the performance of a slow SQL query?
Here's some strategies that can generally speed up a slow SQL query:
- Only query the columns you actually need
- Index the columns used in the query
- Use the right kind of JOIN (be explicit about inner vs. outer joins)
- Use the right data types (for example INT vs BIGINT can save you disk space and memory)
While there's an entire industry dedicated to database performance tuning , for Data Analyst and Data Science interviews at Wayfair, knowing the above basics should be more than enough to ace the SQL interview! Data Engineers on the other hand should know more about the command and understand a bit more about a query-execution plan.
SQL Question 4: Analyzing Product Sales and Returns
As a data analyst at Wayfair, you are tasked with understanding the sales dynamics and product return trends. Your goal is to design a model where you will have a 'sales' table representing every product sold and a 'returns' table representing every product returned.
Using these tables, write a SQL query to find the product with the most returns in each category.
Example Input:
Example Input:
Answer:
This query first calculates the total quantity returned for each product from the 'returns' table. It then joins this with the 'sales' table to add category information. Finally, it groups by category and product, and selects the product with the max returned quantity in each category.
SQL Question 5: What is a foreign key?
A foreign key is a field in a database table that links to the primary key of another table, establishing a connection between the two tables.
To demonstrate this concept, let's analyze Wayfair's marketing analytics database which stores data from Google Ads campaigns:
:
+------------+------------+------------+------------+ | ad_id | campaign_id| keyword | click_count| +------------+------------+------------+------------+ | 1 | 100 | Wayfair pricing | 10 | | 2 | 100 | Wayfair reviews | 15 | | 3 | 101 | Wayfair alternatives | 7 | | 4 | 101 | buy Wayfair | 12 | +------------+------------+------------+------------+
is a foreign key. It references the of the Google Ads campaign that each ad belongs to, establishing a relationship between the ads and their campaigns. This foreign key allows you to easily query the table to find out which ads belong to a specific campaign, or to find out which campaigns a specific ad belongs to.
It is also possible for a table to have multiple foreign keys that reference different primary keys in other tables. For example, the table could have additional foreign keys for the of the ad group that each ad belongs to, and the of the Google Ads account that the campaigns belong to.
SQL Question 6: Average Purchase Amount for Each Category
In the context of Wayfair, a company selling furniture and home-goods online, we may be interested in finding the average purchase amount for each product category. Given a table detailing each transaction and a table that provides category information for each product, create a SQL query to calculate this average.
Example Input:
| purchase_id | product_id | purchase_date | user_id | purchase_amount |
|---|---|---|---|---|
| 1121 | 7100 | 09/10/2022 00:00:00 | 112 | 200.99 |
| 2910 | 5011 | 09/12/2022 00:00:00 | 331 | 129.00 |
| 3491 | 1852 | 09/18/2022 00:00:00 | 652 | 65.50 |
| 9805 | 7100 | 10/01/2022 00:00:00 | 441 | 198.00 |
| 7108 | 1852 | 10/05/2022 00:00:00 | 341 | 70.99 |
Example Input:
| product_id | product_name | category |
|---|---|---|
| 7100 | "Velvet Sofa" | Furniture |
| 5011 | "Oak Dining Table" | Furniture |
| 1852 | "Pendant Lamp" | Lighting |
Answer:
This query joins the table and the table using the common to both. Once the tables are joined, it groups the data by the on the table. Within each category group, it computes the average from the table. This gives the average purchase amount for each category.
SQL Question 7: What is the process for finding records in one table that do not exist in another?
To discover records in one table that are not present in another, you can utilize a and filter out any values in the right-side table.
For example, say you had a table of Wayfair customers and a 2nd table of all purchases made with Wayfair. To find all customers who did not make a purchase, you'd use the following
This query fetches all rows from the customers table, along with any rows that match in the purchases table. If there is no matching row in the purchases table, values will be returned for all of the right table's columns. The clause then filters out any rows where the purchases.id column is NULL, leaving only customers who have not made a purchase.
SQL Question 8: Average Monthly Sale Price for Products
Wayfair, an online home goods retailer, needs to understand the average selling price of all its products on a monthly basis. Using the provided sales data, write an SQL query that will generate a table listing the months, the product_id, and the average sale price of each product for that month.
For this question, we will consider the following table:
Example Input:
| sale_id | product_id | sale_date | sale_price |
|---|---|---|---|
| 1291 | 701 | 06/08/2022 | 100.00 |
| 2612 | 802 | 06/10/2022 | 200.00 |
| 3703 | 701 | 06/28/2022 | 130.00 |
| 4821 | 802 | 07/26/2022 | 220.00 |
| 5249 | 805 | 07/19/2022 | 150.00 |
You need to return a table in the following format, which lists each month, product, and the corresponding average sale price:
Example Output:
| month | product | avg_sale_price |
|---|---|---|
| 6 | 701 | 115.00 |
| 6 | 802 | 200.00 |
| 7 | 802 | 220.00 |
| 7 | 805 | 150.00 |
Answer:
You can use the function in PostgreSQL to extract the month from the and then group by this, along with the , to get the average for each product in each month.
Here is the PostgreSQL query:
This will return a list of months, the product sold in that month, and the average sale price for the product in that specific month. The query first groups by both month and product, and then calculates the average sale price for each of those groupings. It then orders the result by month and product.
How To Prepare for the Wayfair SQL Interview
Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Wayfair SQL interview is to solve as many practice SQL interview questions as you can!
In addition to solving the above Wayfair SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like FAANG and tech startups.
Each exercise has multiple hints, step-by-step solutions and crucially, there is an interactive SQL code editor so you can right in the browser run your SQL query answer and have it executed.
To prep for the Wayfair SQL interview it is also useful to practice SQL problems from other tech companies like:
In case your SQL coding skills are weak, don't worry about diving straight into solving questions – strengthen your SQL foundations with this DataLemur SQL tutorial.
This tutorial covers things like sorting data with ORDER BY and functions like SUM()/COUNT()/AVG() – both of which show up routinely during SQL interviews at Wayfair.
Wayfair Data Science Interview Tips
What Do Wayfair Data Science Interviews Cover?
Beyond writing SQL queries, the other question categories covered in the Wayfair Data Science Interview are:
- Statistics & Probability Questions
- Python Pandas or R Coding Questions
- Product Metrics Interview Questions
- ML Interview Questions
- Behavioral Based Interview Questions
How To Prepare for Wayfair Data Science Interviews?
The best way to prepare for Wayfair Data Science interviews is by reading Ace the Data Science Interview. The book's got:
- 201 Interview Questions from Google, Microsoft & tech startups
- A Crash Course covering Stats, SQL & ML
- Amazing Reviews (900+ 5-star reviews on Amazon)