# 9 Newell Brands SQL Interview Questions (Updated 2024)

Updated on

August 11, 2024

Data Science, Data Engineering and Data Analytics employees at Newell Brands write SQL queries to analyze consumer behavior trends by studying purchase frequency, product preferences, and seasonal fluctuations. They also optimize supply chain processes by analyzing production schedules, inventory turnover, and logistics costs for products across diverse sectors, which is why Newell Brands uses SQL questions during job interviews.

So, to help you study, here’s 9 Newell Brands SQL interview questions – able to answer them all?

## 9 Newell Brands SQL Interview Questions

### SQL Question 1: Calculate Average Monthly Review Ratings Per Product

In Newell Brands, where a variety of consumer and commercial product brands are under management, it is essential to monitor the customer reviews on the product lines. Your task here is to write a SQL query that retrieves the average star review per product on a monthly basis. The review month is determined by the submit_date column.

#### Example Input:

review_iduser_idsubmit_dateproduct_idstars
61711232022-06-08500014
78022652022-06-10698524
52933622022-06-18500013
63521922022-07-26698523
45179812022-07-05698522

Here's the PostgreSQL query to calculate the average star review per product per month:

The above query performs the following operations:

• Extracts the month from the submit_date column.
• Groups the data by both product_id and the review_month.
• Calculates the average of the stars column for each grouping.
• Orders the result by review_month and then by product_id for clear presentation.

#### Example Output:

review_monthproduct_idavg_stars
6500013.5
6698524.0
7698522.5

For more window function practice, solve this Uber SQL problem on DataLemur's online SQL code editor:

### SQL Question 2: Top Department Salaries

Given a table of Newell Brands employee salary information, write a SQL query to find the top 3 highest earning employees within each department.

#### Newell Brands Example Input:

employee_idnamesalarydepartment_id
1Emma Thompson38001
2Daniel Rodriguez22301
3Olivia Smith20001
4Noah Johnson68002
5Sophia Martinez17501
8William Davis68002
10James Anderson40001

#### Example Input:

department_iddepartment_name
1Data Analytics
2Data Science

#### Example Output:

department_namenamesalary
Data AnalyticsJames Anderson4000
Data AnalyticsEmma Thompson3800
Data AnalyticsDaniel Rodriguez2230
Data ScienceNoah Johnson6800
Data ScienceWilliam Davis6800

Write a SQL query for this problem and run your code right in DataLemur's online SQL environment:

We use the DENSE_RANK() window function to generate unique ranks for each employee's salary within their department, with higher salaries receiving lower ranks. Then, we wrap this up in a CTE and filter the employees with a ranking of 3 or lower.

If the code above is tough, you can find a step-by-step solution with hints here: Top 3 Department Salaries.

### SQL Question 3: Can you define what a database index is, and give some examples of different types of indexes?

A database index is a data structure that improves the speed of data retrieval operations on a database table.

There are few different types of indexes that can be used in a database:

• Primary index: a unique identifier is used to access the row directly.
• Unique index: used to enforce the uniqueness of the indexed columns in a table.
• Composite index: created on multiple columns of a table, is used to speed up the search process for multiple columns
• Clustered index: determines the physical order of the data in a table

For a concrete example, say you had a table of Newell Brands customer payments with the following columns:

Here's what a clustered index on the column would look like:

A clustered index on the column would determine the physical order of the records in the table based on the . This means that the records with the earliest values would be stored together physically in the table, followed by records with later payment_date values. This speeds up queries that filter or sort the data based on the , as the records are already physically sorted in the table. For example, if you want to retrieve all the payments made in the month of June, the database can use the clustered index to quickly locate and retrieve the desired records without having to search through the entire table.

### SQL Question 4: Analyzing Product Sales Distribution Across Various Sales Channels

Newell Brands, a global consumer goods company with a broad portfolio, sells its products through multiple channels – online stores, physical retail stores, and wholesale. The company wants to analyze the distribution of product sales across these various channels. This will help the company to better understand its sales trend and optimize resource allocation for different channels accordingly.

The company has the following tables:

##### Example Input:
product_idproduct_namecategory
5678Pencil SharpenerStationery
3456Baby StrollerBaby Products
7890LunchboxHome Goods
##### Example Input:
sale_idproduct_idchannelsale_dateunits_sold
15678Online2022-01-01100
23456Retail2022-01-02250
37890Wholesale2022-01-03500
43456Online2022-01-04300
55678Retail2022-01-05150

The task is to design a PostgreSQL query that will output the total units sold for each product across each channel.

This query joins the table with the table through the field. It uses the GROUP BY clause to group the sales data by product and channel, and then it sums the units_sold for each group. This gives a result showing the total units sold for each product across each channel. This will help the company analyze its sales performance across different channels and optimize its marketing and sales strategies accordingly.

### SQL Question 5: When would you use denormalization?

Denormalization is the practice of altering a database schema in a way that breaks the normalization rules (1st, 2nd, 3rd normal forms).

A few reasons to denormalize a database:

• Improved performance: Denormalization often reduces the the number of costly join operations that are needed to retrieve data. This is helpful when the database is being used for OLAP (Online Analytical Processing) use cases at Newell Brands, as joins can be expensive and slow.

• Scalability: Denormalization can be like a turbo boost for your database's scalability! By requiring less data to be read and processed when executing a query, denormalization can help your database handle a ton of queries without breaking a sweat.

• Simplification: One way to simplify the design of a database is by using denormalization to reduce the number of tables and relationships that need to be managed. This can make the database easier to understand and maintain.

Of course, don't over-do the database denormalization magic – too much redundancy can increase data storage costs, and get complicated to manage if there's frequent commands that need to be run.

### SQL Question 6: Filter the customers who have purchased "Kitchenware" category products, live in "New York", and their last purchase was over a year ago

Newell Brands has a diverse inventory of products like home appliances, cookware, commercial products and baby items. Currently, the company wants to run a marketing campaign specifically targeting customers in New York who have previously purchased Kitchenware products. However, the campaign is intended only for customers who haven't made a purchase in over a year. Write a SQL query to fetch these customers.

##### Example Input:
product_idproduct_namecategory
1001PotKitchenware
1002Frying PanKitchenware
1003Cutlery SetKitchenware
1004Baby BottleBaby Products
1005Animal Soft ToyBaby Products
##### Example Input:
customer_idfirst_namelast_namecity
501JohnDoeNew York
502JaneSmithNew York
503SamGreenBoston
504KateJohnsonChicago
505EmilyBrownNew York
##### Example Input:
order_idcustomer_idproduct_idorder_date
2001501100106/15/2020
2002502100207/20/2019
2003503100110/05/2021
2004504100408/30/2022
2005505100301/18/2020

This SQL query joins the three tables "customers", "orders" and "products". It then filters the result based on the conditions mentioned - customers residing in New York, who have purchased Kitchenware and haven't made any purchase in the last year. The GROUP BY clause ensures that each customer appears only once in the result set.

### SQL Question 7: What does the operator do?

The / operator is used to remove to return all rows from the first SELECT statement that are not returned by the second SELECT statement.

Note that is available in PostgreSQL and SQL Server, while MINUS is available in MySQL and Oracle (but don't stress about knowing which DBMS supports what exact commands since the interviewers at Newell Brands should be lenient!).

Here's a PostgreSQL example of using EXCEPT to find all of Newell Brands's Facebook video ads with more than 10k views that aren't also being run on YouTube:

If you want to retain duplicates, you can use the EXCEPT ALL operator instead of EXCEPT. The EXCEPT ALL operator will return all rows, including duplicates.

### SQL Question 8: Find the average product sales per month for each product

Given the sales data for Newell Brands, can you write an SQL query to find the average product sales in each month for each product? Use the GROUP BY statement along with the AVG aggregate function.

Consider the table below:

##### Example Input:
sales_idproduct_idmonthsales
10050001January100
10169852January225
10250001February150
10369852February200
10450001March75
10569852March250

You need to output a table which shows the average sales for each product for each month.

##### Example Output:
monthproduct_idavg_sales
January50001100.00
January69852225.00
February50001150.00
February69852200.00
March5000175.00
March69852250.00

Here is the PostgreSQL query to solve this problem:

This query groups the sales records by month and product_id. It then calculates the average sales for each group (which correspond to a specific month and product) by using the AVG() function. It finally sorts the result set by month and product_id.

### SQL Question 9: Find Products with Names that Start with 'W'

At Newell Brands, we have numerous products spanning various categories. One of your tasks as a data analyst is to filter out and study specific subsets of these products based on certain characteristics.

For instance, imagine you get a request from the marketing department asking for data about all products in the 'Writing' category that start with the letter 'W'. To tackle this request, you'll need to be skilled at pattern matching using SQL.

Let's assume that the products are recorded in a table called as shown below:

##### Example Input:
product_idproduct_namecategory
1001Wite-Out Correction FluidWriting
2001Waterman Fountain PenWriting
3001Scotch TapeHome Solutions
4001Elmer's GlueSchool Supplies
5001Paper Mate Flair Felt Tip PensWriting
6001Watercolor Paint SetArts & Crafts

The output should be a table listing the product IDs and names of all products in the 'Writing' category that start with the letter 'W'.

Your SQL query could look something like this:

This query first selects the and columns from the table. The clause then filters the rows, including only those where the is 'Writing' and the starts with 'W' (which is what the pattern represents).

If the database is set up as described and the query runs correctly, it should yield the following output:

##### Example Output:
product_idproduct_name
1001Wite-Out Correction Fluid
2001Waterman Fountain Pen

### How To Prepare for the Newell Brands SQL Interview

The best way to prepare for a Newell Brands SQL interview is to practice, practice, practice. Beyond just solving the earlier Newell Brands SQL interview questions, you should also solve the 200+ SQL exercises on DataLemur which come from companies like Microsoft, Google, and Meta.

Each problem on DataLemur has hints to guide you, detailed solutions and most importantly, there's an online SQL coding environment so you can instantly run your SQL query and have it checked.

To prep for the Newell Brands SQL interview you can also be a great idea to practice SQL problems from other consumer good companies like:

Dive into how Newell Brands leverages AI-powered automation to streamline their customer service operations!

However, if your SQL query skills are weak, forget about diving straight into solving questions – improve your SQL foundations with this DataLemur SQL tutorial.

This tutorial covers SQL topics like aggreage functions like MIN()/MAX() and Self-Joins – both of these show up routinely during SQL job interviews at Newell Brands.

### Newell Brands Data Science Interview Tips

#### What Do Newell Brands Data Science Interviews Cover?

Besides SQL interview questions, the other question categories to prepare for the Newell Brands Data Science Interview include:

#### How To Prepare for Newell Brands Data Science Interviews?

To prepare for the Newell Brands Data Science interview make sure you have a firm understanding of the company's values and mission – this will be important for acing the behavioral interview. For technical interviews prepare by reading Ace the Data Science Interview. The book's got:

• 201 Interview Questions from Google, Microsoft & tech startups
• A Refresher covering Product Analytics, SQL & ML
• Amazing Reviews (1000+ reviews, 4.5-star rating)