# 8 Samsung SQL Interview Questions (Updated 2024)

Updated on

February 7, 2024

At Samsung, SQL is core to their business. They support developers writing SQL queries if they want to query Samsung IoT & automation products, and also have their own DB-as-a-service cloud offering. Because of this, Samsung frequently asks SQL coding questions in interviews for Data Science, Data Engineering and Data Analytics jobs.

In case you're stressed about an upcoming SQL Interview, we've curated 8 Samsung SQL interview questions to practice, which are similar to commonly asked questions at Samsung – how many can you solve?

## 8 Samsung SQL Interview Questions

### SQL Question 1: Calculate the average product rating per month

As part of the Product Development team at Samsung, you are given the task to analyze customer feedback on the HUGE product catalog Samsung has. Each product is identified by a unique product_id, and every time a customer rates a product, a new record is created in the 'reviews' table with the associated customer's user_id, the timestamp of the review (submit_date), the product they reviewed (product_id) and the rating they gave (stars).

Your task is to write a SQL query to calculate the average rating (stars) for each product per month. The 'submit_date' is saved in the 'YYYY-MM-DD HH:MI:SS' format.

##### Example Input:
review_iduser_idsubmit_dateproduct_idstars
61711232022-06-08 00:00:00500014
78022652022-06-10 00:00:00698524
52933622022-06-18 00:00:00500013
63521922022-07-26 00:00:00698523
45179812022-07-05 00:00:00698522

##### Example Output:
mthproduct_idavg_stars
6500013.50
6698524.00
7698522.50

This SQL query groups the reviews by month and product and calculates the average stars for each group. The query uses the function to extract the month part of the , and the function to calculate the average stars. The clause groups the rows that have the same values in specified columns into aggregated data. Lastly, the clause is used to sort the result set in ascending or descending order, based on one or more columns, which in this case are 'mth' and 'product_id'.

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

### SQL Question 2: Analyze Galaxy Smartphone Sales Data

Samsung is interested in analyzing the Galaxy Smartphone sales data. They have their sales data across different regions and across different Galaxy models. Samsung would like to know which model is the most popular in each region based on the number of units sold.

Please design the database tables that would cater to this situation: a table for regions, a table for smartphone models, and a table for sales recording.

Also write a SQL query that outputs the most popular smartphone model by region based on the total number of units sold.

Here are our tables:

#### Example Input:

region_idregion_name
1North America
2South America
3Europe
4Asia

#### Example Input:

model_idmodel_name
1Galaxy S21
2Galaxy S21 Ultra
3Galaxy Note20
4Galaxy Z Fold2

#### Example Input:

sale_idregion_idmodel_idunits_sold
111500
212700
313300
421600
523800
6321000
7442000

This query joins the , and table and sums up the grouped by and . The result is then ordered by and in descending order to see the most popular models by region at the top. undefined

### SQL Question 3: Can you explain the distinction between a clustered and a non-clustered index?

A clustered index is an index where the order of the rows in the database corresponds to the order of the rows in the index. Because of this, a table can only have one clustered index, but it can have multiple non-clustered indexes.

The main difference between the two is that the database tries to keep the data in the same order as the corresponding keys in the clustered index. This can improve the performance of most query operations, as it provides a linear-access path to the data stored in the database.

### SQL Question 4: Filter Samsung Customers Based on Purchases and Customer Status

As a Samsung data analyst, you are given the task to filter the data of their customers. Your goal is to find out customers who have purchased the Samsung Galaxy S21 smartphone in the year 2022 and are signed up for the Samsung Members program, then show their contact details for promotional email campaign.

In the 'purchases' table, 'product' column values corresponding to the Samsung Galaxy S21 is 'S21'. The 'year' column is for the purchase year, and 'user_signed_up' column denotes if the customer is signed up for the Samsung Members program, 1 being true and 0 being false.

#### Example Input:

customer_idnameemailuser_signed_up
9615James Smithjames_smith@email.com1
7021Samantha Brownsamantha_brown@email.com1
8523John Doejohn_doe@email.com0
6405Anna Johnsonanna_johnson@email.com1
9347Emma Blackemma_black@email.com0

#### Example Input:

purchase_idcustomer_idproductyear
51719615S212022
78027021S212022
82358523Note202022
63206405S212021
73959347S212022

#### Example Output:

nameemail
James Smithjames_smith@email.com
Samantha Brownsamantha_brown@email.com

The above SQL query joins the 'customers' and 'purchases' tables based on 'customer_id'. It then filters out customers who have purchased the Samsung Galaxy S21 in 2022 and are in the Samsung Members program based on the WHERE conditions. The result is a list of their names and email addresses. undefined

### SQL Question 5: What do the / operators do, and can you give an example?

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 Samsung should be lenient!).

For a tangible example in PostgreSQL, suppose you were doing an HR Analytics project for Samsung, and had access to Samsung's contractors and employees data. Assume that some employees were previously contractors, and vice versa, and thus would show up in both tables. You could use operator to find all contractors who never were a employee using this query:

### SQL Question 6: Calculate the Average Sale Price for Each Samsung Products

As a Data Analyst at Samsung, you are asked to analyze the sale data. For each product, calculate the average sale price per month, for the year 2022. Assume today is July 31st, 2022.

Below are the sample tables for your analysis:

##### Example Input:
sale_idproduct_idsale_dateprice
311219012301/21/2022899.99
423516053202/14/2022349.00
578319012303/13/2022879.99
646895382104/25/2022699.99
776525382106/20/2022689.00
897126053207/05/2022359.99
##### Example Output:
monthproduct_idavg_price
190123899.99
260532349.00
390123879.99
453821699.99
653821689.00
760532359.99

This SQL query first extracts the month and year from the field. It then groups the data by and , and calculates the average price for each group. The clause ensures we're only looking at the sales data for the year 2022. The clause sorts the results by and then . undefined

### SQL Question 7: How do cross joins and natural joins differ?

A cross join is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. It is also known as a cartesian join.

For example, say you worked on the Marketing Analytics team at <comapany_name>, 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:

A natural join, on the other hand, is a type of JOIN that combines rows from two or more tables based on their common columns. It is called a "natural" join because it is based on the natural relationship that exists between the common columns in the tables being joined.

For an example of each one, say you had sales data exported from Samsung's Salesforce CRM stored in a datawarehouse which had two tables: and .

An (which is a type of natural join) combines the two tables on the common

This query will return rows from the sales and tables that have matching customer id values. Only rows with matching values will be included in the results.

One main difference between cross joins and natural joins is that cross joins do not require any common columns between the tables being joined, while natural joins do. Another difference is that cross joins can create very large tables if the input tables have a large number of rows, while natural joins will only return a table with the number of rows equal to the number of matching rows in the input tables.

### SQL Question 8: Finding all customers who bought 'Galaxy' series

You are the Data Analyst at Samsung and your manager has asked you to find all customers who have purchased from the 'Galaxy' series. Samsung has multiple product lines but you are only interested in customers who purchased any product with 'Galaxy' in its product name. For this task, use the 'customers' and 'products' tables. The 'products' table has a column called 'product_name' where all the product names are stored.

##### Example Input:
customer_idfirst_namelast_name
123JohnDoe
265SophiaBrown
362LiamSmith
192AvaJohnson
981NoahThompson
##### Example Input:
product_idproduct_namecustomer_id
50001Galaxy S21123
69852IPhone 13265
25035Galaxy Note10362
54603Z Flip3192
56310Galaxy Z Fold3981

You can filter the data by using the SQL keyword LIKE with the '%' wildcard character to filter records that include 'Galaxy' anywhere in the product name. Your query should look like this:

This query will join the customers and products tables on the 'customer_id' column and filter the record to only include rows where the product name includes 'Galaxy'. The output will be a list of customers who have purchased a product with 'Galaxy' in its product name. undefined

### How To Prepare for the Samsung SQL Interview

The best way to prepare for a Samsung SQL interview is to practice, practice, practice. In addition to solving the above Samsung SQL interview questions, you should also solve the 200+ SQL questions from real Data Science & Analytics interviews which come from companies like Netflix, Airbnb, and Amazon.

Each SQL question has multiple hints, fully explained answers along with a discussion board to see how others solved it and most importantly, there is an interactive SQL code editor so you can right in the browser run your SQL query answer and have it checked.

To prep for the Samsung SQL interview you can also be wise to practice interview questions from other tech companies like:

In case your SQL foundations are weak, don't worry about jumping right into solving questions – improve your SQL foundations with this free SQL for Data Analytics course.

This tutorial covers things like window functions like RANK() and ROW_NUMBER() and math functions like ROUND()/CEIL() – both of these show up frequently in SQL job interviews at Samsung.

### Samsung Data Science Interview Tips

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

For the Samsung Data Science Interview, in addition to SQL query questions, the other types of questions to practice:

• Probability & Stats Questions
• Coding Questions in Python or R
• Business Sense and Product-Sense Questions
• Machine Learning and Predictive Modeling Questions
• Behavioral & Resume-Based Questions

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

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