# 10 Netflix SQL Interview Questions (Updated 2024)

Updated on

February 7, 2024

At Netflix, SQL crucial for analyzing streaming statistics to identify viewing trends and to analyze data from A/B testing. Unsurprisingly this is why Netflix frequently asks advanced SQL problems during interviews for Data Science and Data Engineering positions.

To help you prepare, this blog covers 10 Netflix SQL interview questions to practice, which are similar to recently asked questions at Netflix – able to answer them all?

## 10 Netflix SQL Interview Questions

### SQL Question 1: Identify VIP Users for Netflix

To better cater to its most dedicated users, Netflix would like to identify its "VIP users" - those who are most active in terms of the number of hours of content they watch. Write a SQL query that will retrieve the top 10 users with the most watched hours in the last month.

##### Example Input Table
user_idsign_up_datesubscription_type
43508/20/2020Standard
52909/15/2021Basic
69212/28/2021Standard
##### Example Input Table
activity_iduser_iddate_timeshow_idhours_watched
1035543502/09/2022 12:30:00120012.5
1487227802/10/2022 14:15:00172851.2
1229352902/18/2022 21:10:00120014.3
1635269202/20/2022 19:00:00172853.7
1748572902/25/2022 16:45:00172851.9

The given query joins the 'users' and 'watching_activity' tables and calculates the total hours watched by each user within the last month. It then sorts these users in order of most hours watched and takes the top 10 results.

To practice a similar power-user data analysis problem question on DataLemur's free online SQL coding environment, try this recently asked Microsoft SQL interview question:

### SQL Question 2: Analyzing Ratings For Netflix Shows

Given a table of user ratings for Netflix shows, calculate the average rating for each show within a given month. Assume that there is a column for user id, show id, rating (out of 5 stars), and date of review. Order the results by month and then by average rating (descending order).

This is will provide an interesting insights into how show ratings fluctuate over time and which shows have garnered the most positive feedback.

Sample Tables:

##### Example Input:
review_iduser_idreview_dateshow_idstars
617112306/08/2022 00:00:00500014
780226506/10/2022 00:00:00698524
529336206/18/2022 00:00:00500013
635219207/26/2022 00:00:00698523
451798107/05/2022 00:00:00698522
##### Example Output:
mthshow_idavg_stars
6500013.50
6698524.00
7698522.50

Your SQL query could look like this:

This query pulls out the month from the review_date, groups the data by month and show_id, and for each group, calculates the average stars. The results are then ordered first by month, then by average stars in a descending order (highest rated shows first).

p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

### SQL Question 3: What does / SQL commands 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 Netflix should be lenient!).

Here's a PostgreSQL example of using EXCEPT to find all of Netflix'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 4: Filter Netflix Users Based on Viewing History and Subscription Status

You are given a database of Netflix's user viewing history and their current subscription status. Write a SQL query to find all active customers who watched more than 10 episodes of a show called "Stranger Things" in the last 30 days.

For this question, consider the following tables:

user_idactive
1001true
1002false
1003true
1004true
1005false
##### Example Input:
user_idshow_idepisode_idwatch_date
1001200130012022-10-01
1001200130022022-10-02
1001200130032022-10-03
1002200130012022-10-01
1002200130022022-10-02
1003200130012022-10-01
1003200130022022-11-01
1003200130032022-11-02
1004200230042022-11-03
##### Example Input:
show_idshow_name
2001"Stranger Things"
2002"Money Heist"

In PostgreSQL, the SQL query to solve the above problem would be:

The SQL query starts by joining the table with on the column and then joins with the table on .

It then uses a WHERE clause to filter for active users and the show "Stranger Things", and limits the to the last 30 days.

The GROUP BY statement groups the result by , and the HAVING clause filters the groups that have more than 10 unique 's, or in other words, customers that have viewed more than 10 episodes. undefined

### SQL Question 5: What does it mean to denormalize a database?

Denormalization is the process of modifying a database schema in a way that deviates from the typical rules of normalization (1NF, 2NF, 3NF, etc.).

Denormalization is often used to improve the performance of a database, particularly when it is being used for reporting and analytical purposes (rather than in an Online Transaction Processing (OLTP) manager).

By duplicating data, denormalization can reduce the number of expensive joins required to retrieve data, which can improve query performance. However, denormalization can also cause problems such as increased data redundancy and the need for more complex update and delete operations.

### SQL Question 6: Filter and Match Customer's Viewing Records

As a data analyst at Netflix, you are asked to analyze the customer's viewing records. You confirmed that Netflix is especially interested in customers who have been continuously watching a particular genre - 'Documentary' over the last month.

The task is to find the name and email of those customers who have viewed more than five 'Documentary' movies within the last month.

'Documentary' could be a part of a broader genre category in the genre field (for example, 'Documentary, History'). Therefore, the matching pattern could occur anywhere within the string.

Use the and databases provided below:

##### Example Input
movie_idtitlegenrerelease_year
1265'The Last Dance''Documentary, Sport'2020
7821'Tiger King''Documentary, Crime'2020
3402'Becoming''Documentary'2020
5698'Swift'Documentary, Music'2020
4169'The Irishman''Biography, Crime, Drama'2019
2698'Extraction''Action, Thriller'2020

Example Input:

user_idnameemaillast_movie_watcheddate_watched
361'John Doe''johndoe@gmail.com'1265'2021-08-03'
124'Jane Smith''janesmith@yahoo.com'1265'2021-08-03'
815'Emily Clark''emilyclark@hotmail.com'7821'2021-08-03'
634'Robert Brown''robertbrown@gmail.com'3402'2021-08-03'
962'Sarah Johnson''sarahjohnson@gmail.com'5698'2021-08-03'

In the SQL query above, we are joining and tables on the and fields. We retrieve the and from the table who have watched more than 5 movies in the genre 'Documentary' in the last month. We use the PostgreSQL operator combined with the wildcard to match customers who have the genre 'Documentary' listed anywhere in the field. We use GROUP BY and HAVING to consider only those customers who have viewed more than five documentaries within the last month. This query will return the name and email of those customers. undefined

### SQL Question 7: Can you explain the concept of database normalization?

Database normalization is the process of breaking down a table into smaller and more specific tables and defining relationships between them via foreign keys. This minimizes redundancy, and creates a database that's more flexible, scalable, and easier to maintain. It also helps to ensure the integrity of the data by minimizing the risk of data inconsistencies and anomalies.

### SQL Question 8: Analyzing Netflix User Behavior and Content Ratings

You're a Data Analyst at Netflix, you have been asked to analyze customer behavior and their content ratings. You have the following two tables:

• A table that has information about users, their ID and their subscription_starts.
• A table that has information about what content each user has reviewed and the score they gave.

Write a SQL query to analyze the data and find the average rating for each content, sorted by the average rating in descending order.

#### Example tables:

##### Example Input:
user_idsubscription_starts
12018-01-01
22019-02-20
32017-07-14
42020-11-28
52018-04-24
##### Example Input:
review_iduser_iddatecontent_idrating
10112022-06-0814
20222022-06-1024
30332022-06-1813
40412022-07-2623
50552022-07-0512

This query first joins users table with reviews table on user_id. Then, it groups by in reviews table and calculates the average rating for each content. Finally, it sorts the resulting data by in descending order, so that the content with the highest average rating will be at the top.

Since joins come up so often during SQL interviews, try this interactive Snapchat SQL Interview question using JOINS:

### SQL Question 9: Calculate the Standard Deviation of Movie Ratings

Netflix wants to have a better understanding of how their ratings vary for each movie department. They want to calculate the standard deviation of ratings given to the movies of various departments.

The standard deviation is a measure of how spread out the ratings are. If the ratings are all close to the mean, the standard deviation is close to zero. If the ratings are spread out over a wider range, the standard deviation is larger.

The standard deviation is calculated by taking the square root of the variance. Variance is calculated as follows: the difference between each rating and the mean rating is squared, these squared differences are averaged, this produces the variance.

Utilize the ratings provided by users and apply SQL functions like AVG(), POWER(), SQRT() to compute the standard deviation.

Assuming you have a table named like below:

##### Example Input:
movie_iddepartment_idrating
10012004
10022005
10032013
10042022
10052002
10062025
10072011
10082024

In the query above, the inner query computes the average rating per each department. This average rating (the "mean") is needed to compute the variance.

The outer query calculates the variance by subtracting the mean from each rating, squaring the result and taking the average of these squares. The square root of this variance gives us the standard deviation. This query provides the standard deviation of movie ratings for each department.

To practice a very similar question try this interactive Amazon Average Review Ratings Question which is similar for calculating statistical measures or this Alibaba Compressed Mean Question which is similar for understanding spread of data.

### SQL Question 10: What is a foreign key?

A foreign key is a column or group of columns in a table that refers to the primary key in another table. The foreign key constraint helps maintain referential integrity between the two tables.

For example, let's look at the Netflix sales database:

netflix_sales:

+------------+------------+------------+------------+ | order_id | product_id | customer_id| quantity | +------------+------------+------------+------------+ | 1 | 222 | 1 | 2 | | 2 | 333 | 1 | 1 | | 3 | 444 | 2 | 3 | | 4 | 555 | 3 | 1 | +------------+------------+------------+------------+

In this table, 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.

### Netflix SQL Interview Tips

The key to acing a Netflix SQL interview is to practice, practice, and then practice some more! Besides solving the above Netflix SQL interview questions, you should also solve the 200+ SQL coding questions which come from companies like Amazon, Microsoft, Meta, and smaller tech companies.

Each problem on DataLemur has hints to guide you, fully explained answers along with a discussion board to see how others solved it and crucially, there is an interactive coding environment so you can easily right in the browser your SQL query answer and have it checked.

To prep for the Netflix SQL interview you can also be useful to practice SQL problems from other tech companies like:

However, if your SQL query skills are weak, forget about jumping right into solving questions – improve your SQL foundations with this SQL tutorial for Data Analytics.

This tutorial covers SQL concepts such as window functions and finding NULLs – both of these show up often in Netflix SQL interviews.

### Netflix Data Science Interview Tips

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

For the Netflix Data Science Interview, besides SQL questions, the other types of questions to prepare for are:

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

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

• 201 interview questions sourced from Microsoft, Amazon & startups
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• over 900+ reviews on Amazon & 4.5-star rating