Netflix Analytics Engineer Interview Experience:


SQL Questions:

1️⃣ SQL Question 1: Identify VIP Users for Netflix

Question: 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.

Tables:
• users table: user_id (integer), sign_up_date (date), subscription_type (text)
• watching_activity table: activity_id (integer), user_id (integer), date_time (timestamp), show_id (integer), hours_watched (float)

2️⃣ SQL Question 2: Analyzing Ratings For Netflix Shows

Question: 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).

Tables:
• show_reviews table: review_id (integer), user_id (integer), review_date (timestamp), show_id (integer), stars (integer)

3️⃣ SQL Question 3: What does EXCEPT / MINUS SQL commands do?

Question: Explain the purpose and usage of the EXCEPT (or MINUS in some SQL dialects) SQL commands.

4️⃣ SQL Question 4: Filter Netflix Users Based on Viewing History and Subscription Status

Question: 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.

Tables:
• users table: user_id (integer), active (boolean)
• viewing_history table: user_id (integer), show_id (integer), episode_id (integer), watch_date (date)
• shows table: show_id (integer), show_name (text)

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

Question: Explain the concept and implications of denormalizing a database.

6️⃣ SQL Question 6: Filter and Match Customer’s Viewing Records

Question: 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.

Tables:
• movies table: movie_id (integer), title (text), genre (text), release_year (integer)
• customer table: user_id (integer), name (text), email (text), last_movie_watched (integer), date_watched (date)

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