📚 100 DAYS SQL
CODING CHALLENGE

🎬 Netflix Movies Analytics

Build a streaming analytics platform with rankings, window functions, complex JOINs, and CTEs.

Table 1: movies (5 of 50 rows)

movie_id	title	release_year	duration_mins	language	budget_millions	revenue_millions
M001	inception	2010	148	english	160	829.9
m002	THE DARK KNIGHT	2008	NULL	English	185	1005.5
M003	parasite	2019	132	korean	NULL	258.8
M004	avengers endgame	2019	181	ENGLISH	356	2798.5
m005	Titanic	1997	195	English	200	NULL

...45 more rows in the download!

Table 2: genres

genre_id	movie_id	genre_name
G001	M001	Sci-Fi
G002	m001	action
G003	M002	ACTION
G004	M003	thriller

Table 3: actors (5 of 50 rows)

actor_id	actor_name	birth_year	nationality
A001	leonardo dicaprio	1974	american
a002	CHRISTIAN BALE	NULL	British
A003	Song Kang-ho	1967	south korean

Table 4: movie_cast

cast_id	movie_id	actor_id	role_type	character_name
C001	M001	A001	LEAD	Dom Cobb
C002	m002	a002	lead	Batman

Table 5: user_ratings (5 of 50 rows)

rating_id	movie_id	user_id	rating	rating_date
R001	M001	U101	8.5	2024-01-15
R002	m001	U102	9.0	15/01/2024

📋 Your Challenge

Build Netflix analytics with rankings, percentiles, ROI calculations, and complex multi-table JOINs.

💡 Key SQL Concepts: RANK, ROW_NUMBER, PERCENT_RANK, PARTITION BY, CTEs, Complex JOINs, GROUP_CONCAT!