SQL Practice Log: Movie Data, Date Filtering, and Real-World Queries

Introduction

Today I practiced SQL using various real datasets — including one based on movies (SAKILA), and others with date-specific filters.
Instead of just focusing on syntax, I tried to treat it like real-world data analysis. This post summarizes what I did, what worked, and what confused me.

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The Problem

I had three goals in mind:

1. Query movie data with conditions and ordering
2. Filter based on date formats (e.g. specific months)
3. Use JOIN, GROUP BY, and subqueries in a meaningful way

To do this, I used multiple .sql files and ran queries in DBeaver against structured tables.

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What I Practiced

Movie Query (SAKILA)

• Selected movie titles and filtered by rental rate
• Ordered results with multiple conditions

SELECT title, rental_rate
FROM film
WHERE rental_rate >= 4.99
ORDER BY title DESC, rental_rate DESC;

Filtering by Month

In a file with 2024 date data, I tried filtering by month value using MONTH():

SELECT *
FROM orders
WHERE MONTH(order_date) = 5;

This helped isolate May-specific data regardless of the year.

Grouping & Having

I also worked with GROUP BY and HAVING to count or limit groups:

SELECT customer_id, COUNT(*) AS order_count
FROM orders
GROUP BY customer_id
HAVING order_count >= 5;

This was useful to detect power users — customers who ordered more than five times.

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What I Learned

• How to sort results with multiple ORDER BY conditions
• Why HAVING is used after GROUP BY (not WHERE)
• How to pull only a specific month’s data with MONTH(date_column)
• COUNT(*) with GROUP BY can reveal patterns I never saw with basic filters

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What I Thought About

I realized that:

• SQL gets powerful not when you know every command, but when you combine them effectively
• Realistic datasets (like movies, orders, rentals) make practicing fun and more memorable
• Reading and modifying example queries helped me learn faster than starting from scratch

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What I Want to Do Next

• Try building my own mini database (like a book store or music library) and write queries from scratch
• Learn window functions (RANK, ROW_NUMBER, OVER())
• Practice writing subqueries that return useful summaries

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SQL isn’t just about querying — it’s about thinking like an analyst.
And today, I felt like I took one more step in that direction.