# 11 Mattel SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

Data Scientists, Analysts, and Data Engineers at Mattel uses SQL to analyze sales data, such as tracking toy sales by region and season, for profitable toy trends. it is also used to manage warehousing, including optimizing inventory levels and streamlining logistics, for efficient supply chain operations, which is why Mattel uses SQL questions for job interviews.

To help you study for the Mattel SQL interview, here's 11 Mattel SQL interview questions in this blog.

## 11 Mattel SQL Interview Questions

### SQL Question 1: Product Sales and Average Rating Analysis

For the toy manufacturer Mattel, you have been provided with two tables. One table is which lists general product information and another table that provides customer's review details. Your task is to write a SQL query that can compute the average customer reviews for each product for each month and the product's total sales per month.

Note: We are assuming that each review is associated with a single product purchase.

Here are the sample tables:

##### Table:
product_idproduct_namelaunch_dateprice
101Toy Car01/01/202120
102Doll House05/01/202150
103Action Figure07/01/202130
##### Table:
review_iduser_idsubmit_dateproduct_idstars
617112306/08/20221024
780226506/10/20221014
529336206/18/20221023
635219207/26/20221013
451798107/05/20221032

In this query, truncates the date to month, so we get reviews and thus sales data grouped by month.

We join with on product_id and then carry out the group by month, product_id, and product_name and order by month, average review rating in descending order and total sales in descending order, essentially sorting the products per month based on highest average rating and if ratings are same then based on highest sales.

The average reviews are cast to decimal(4,2) for precision up to two decimal points.

This query helps identify the products' performance in terms of customer reviews and sales on a per-month basis.

For more window function practice, solve this Uber SQL Interview Question within DataLemur's online SQL coding environment:

### SQL Question 2: Highly-Paid Employees

Given a table of Mattel employee salary information, write a SQL query to find employees who earn more money than their direct manager.

#### Mattel Example Input:

employee_idnamesalarydepartment_idmanager_id
1Emma Thompson38001
2Daniel Rodriguez2230110
3Olivia Smith800018
4Noah Johnson680028
5Sophia Martinez1750110
8William Davis70002NULL
10James Anderson40001NULL

#### Example Output:

employee_idemployee_name
3Olivia Smith

This is the output because Olivia Smith earns \$8,000, surpassing her manager, William Davis who earns 7,800.

Check your SQL query for this question directly within the browser on DataLemur:

First, we perform a SELF-JOIN where we treat the first table () as the managers' table and the second table () as the employees' table. Then we use a clause to filter the results, ensuring we only get employees whose salaries are higher than their manager's salary.

If the solution above is confusing, you can find a detailed solution here: Employees Earning More Than Their Boss.

### SQL Question 3: Name the different types of joins in SQL. What does each one do?

Using a join in SQL, you can retrieve data from multiple tables and merge the results into a single table.

In SQL, there are four distinct types of JOINs. To demonstrate each kind, Imagine you had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

• : An INNER JOIN retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.

• : 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.

• : A FULL OUTER JOIN retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.

### SQL Question 4: Compute the Average Selling Price for Each Toy Category

At Mattel, we have a database tracking sales of every toy sold. This information is useful for our business to calculate the average selling price of each toy category to help us with revenue forecasting and pricing strategy. We have two tables: and . The table captures each transaction and the table stores details about each toy, including its category. Your task is to write an SQL query that computes the average price for each toy category on a monthly basis.

Here's the schema and some sample data for the two tables.

##### Sample Input:
sale_idtoy_idsale_dateprice
110106/08/202220.99
210206/08/202235.99
310106/15/202220.99
410307/01/202225.99
510407/10/202215.99
##### Sample Input:
toy_idtoy_namecategory
101BarbieDolls
102Hot WheelsDie-Cast Vehicles
103Max SteelAction Figures
104UnoCard Games

The query first joins the table with the table on . Then it groups by the month and the toy category, and calculates the average price using the AVG() function. This will give the average price for each toy category on a monthly basis.

#### Example Output:

monthcategoryavg_price
June 2022Dolls20.99
June 2022Die-Cast Vehicles35.99
July 2022Action Figures25.99
July 2022Card Games15.99

### SQL Question 5: Can you describe the difference between a unique and a non-unique index?

While both types of indexes improve the performance of SQL queries by providing a faster way to lookup rows of data, a unique index enforces the uniqueness of the indexed columns, meaning that no duplicate values are allowed in the indexed columns. On the other hand, a non-unique index allows duplicate values in the indexed columns.

Here is an example of a unique index on the column of a table of Mattel employees:

This index would ensure that no two Mattel employees have the same , which could be used as a unique identifier for each employee.

Here is an example of a non-unique index on the column of the same table:

This index would not enforce uniqueness, but it could be used to improve the performance of queries that filter or sort the data based on the column. For example, if you want to retrieve all employees who were Data Analysts, the database can use the index to quickly locate and retrieve the desired records without having to search through all the employees.

### SQL Question 6: Filter Mattel Customers

Suppose you are working with the customer data for Mattel. You need to filter down to customers who made purchases within the last year, live in California, and spent more than \$100 in total. Write an SQL query to return these customer records.

Below are the example input and output data:

##### Example Input:
customer_idstatejoin_date
123California10/10/2020
456New York06/15/2021
789California01/29/2021
##### Example Input:
purchase_idcustomer_idpurchase_dateamount
112305/08/2021\$150
245606/18/2021\$60
312308/10/2021\$50
478910/20/2021\$200
##### Example Output:
customer_idstatetotal_amount
123California\$200
789California\$200

The query joins the and tables based on the common field. It then filters out customers based on their state, amount spent, and recent purchase history. The final output is grouped by customer ID and state, and only those customers who meet all the conditions are returned.

### SQL Question 7: What is a self-join?

A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

For instance, suppose you had website visitor data for Mattel, exported from the company's Google Analytics account. To assist the web-dev team, you needed to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to generate all pairs of URLs, but needed to exclude pairs where both URLs were the same since that is not a valid pair."

You could use the following self-join:

This query returns the url of each page () along with the url of the page that referred to it (). The self-join is performed using the field, which specifies the id of the page that referred the visitor to the current page, and avoids any pages that referred themself (aka data anomalies).

### SQL Question 8: Calculating Click-through-Rate (CTR) for Mattel's Digital Ads

Mattel, a major toy brand, has been running digital advertising campaigns for its products. The company is interested in knowing the Click-through-Rate (CTR) of their ads to evaluate their performance. CTR is calculated as the number of users who clicked on the ad divided by the number of times the ad was shown, expressed as a percentage.

The data you have includes which records each time an ad was shown to a user and which records each time a user clicked on an ad.

##### Example Input:
536230006/08/2022 00:00:0020001
219420106/10/2022 00:00:0020002
498317606/18/2022 00:00:0020001
162530107/26/2022 00:00:0020002
728149207/05/2022 00:00:0020001
##### Example Input:
367130006/08/2022 00:00:0020001
240220106/10/2022 00:00:0020002
193717606/18/2022 00:00:0020001
135430107/26/2022 00:00:0020002

This SQL query calculates the CTR for each ad by dividing the number of distinct clicks by the number of distinct impressions. The result is a float number reflecting the proportion of users who saw the ad and clicked on it.

To practice a similar problem about calculating rates, solve this TikTok SQL question within DataLemur's interactive SQL code editor:

### SQL Question 9: Find the total quantity of each toy sold by Mattel in 2021.

At Mattel, we are interested in knowing which toys are best sellers. Write a SQL query to find out the total quantity of each toy sold by Mattel in the year 2021.

Assume we have the following two tables:

##### Example Input:
product_idproduct_name
101Barbie Doll
102Hot Wheels Car
103Fisher Price Baby Toy
##### Example Input:
sale_idproduct_idsale_datequantity_sold
56710103/12/2021150
56810205/23/2021300
56910310/18/2021400
57010107/26/2021250
57110206/05/2021100

We are interested in the following output:

##### Example Output:
product_nametotal_quantity_sold_in_2021
Barbie Doll400
Hot Wheels Car400
Fisher Price Baby Toy400

This SQL query joins the and tables together, filtering for sales that took place in the year 2021. It then groups results by the product name. The SUM() function is used to calculate total quantity sold for each product in 2021. The output provides us with the total quantity sold for each product in 2021, providing insight into the popularity and demand for various products.

### SQL Question 10: Can you explain the difference between a foreign and primary key in a database?

To explain the difference between a primary key and foreign key, let's start with an example Mattel sales database:

##### :
order_idproduct_idcustomer_idquantity
130312
240411
350523
430331

In this table, could be a primary key. It is unique for each row in the table and cannot contain null values.

and could both be foreign keys. They reference the primary keys of other tables, such as a Products table and a Customers table, respectively. This establishes a relationship between the table and the other tables, such that each row in the sales database corresponds to a specific product and a specific customer.

### SQL Question 11: Find Customers who purchased Barbie Products

Mattel is a company well-known for its Barbie products. You have a list of customer purchases in the "purchases" table. Your task is to locate all customers who have purchased a Barbie product. The LIKE keyword can help you match the product name to a pattern - in specifically, each Barbie product's name begins with 'Barbie'.

Given the following tables, write a SQL command that will locate these customers.

##### Example Input:
customer_idfirst_namelast_name
1JohnDoe
2SallySmith
3MikeJohnson
##### Example Input:
purchase_idcustomer_idproduct_name
11Barbie Dreamhouse
22Hot Wheels Track
33Barbie Convertible
41Uno Card Game
52Barbie Pop Star

The following SQL command can be used to solve the problem:

This command joins 'customers' and 'purchases' tables on 'customer_id'. It selects distinct first and last name from customers where the 'product_name' starts with 'Barbie'. The keyword LIKE is used here along with the pattern 'Barbie%', where % is a wild-card that matches zero or more characters, allowing you to match any product name beginning with 'Barbie'.

### Preparing For The Mattel SQL Interview

The key to acing a Mattel SQL interview is to practice, practice, and then practice some more! Besides solving the earlier Mattel SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like FAANG tech companies and tech startups.

Each exercise has hints to guide you, detailed solutions and best of all, there is an online SQL coding environment so you can instantly run your SQL query and have it graded.

To prep for the Mattel SQL interview it is also helpful to solve SQL questions from other consumer good companies like:

However, if your SQL query skills are weak, don't worry about going right into solving questions – improve your SQL foundations with this DataLemur SQL Tutorial.

This tutorial covers SQL topics like creating pairs via SELF-JOINs and how window functions work – both of these show up frequently during Mattel SQL assessments.

### Mattel Data Science Interview Tips

#### What Do Mattel Data Science Interviews Cover?

In addition to SQL query questions, the other question categories to prepare for the Mattel Data Science Interview include:

Learn how Mattel is driving innovation and creativity in the toy industry with their latest news and announcements!

#### How To Prepare for Mattel Data Science Interviews?

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

• 201 interview questions taken from FAANG, tech startups, and Wall Street
• a refresher on SQL, Product-Sense & ML
• over 1000+ 5-star reviews on Amazon

Also focus on the behavioral interview – prepare for that using this list of common Data Scientist behavioral interview questions.