Film SQL Analytics Project (MySQL)

Project Overview

This project demonstrates SQL-based data analysis using a relational films dataset. The objective is to extract business insights from structured data using analytical SQL queries.

The project simulates real-world reporting and analysis tasks commonly performed by SQL Analysts, Data Analysts, and Database Support professionals.

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Database Structure

Table

films – Stores film information including:

• title
• genre
• release_year
• duration_minutes
• budget_millions
• revenue_millions
• rating

The table is created using SQL Data Definition Language (DDL) and populated with sample data to simulate an analytical reporting database.

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SQL Analytics Capabilities Demonstrated

The project demonstrates core SQL techniques used for data analysis:

• Data retrieval using SELECT
• Record counting using COUNT
• Filtering records using WHERE
• Removing duplicates using DISTINCT
• Sorting results using ORDER BY
• Limiting result sets using LIMIT
• Aggregation using SUM, AVG, MAX, and MIN
• Grouping data using GROUP BY
• Filtering grouped results using HAVING
• Generating business-style reporting queries

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Example Business Questions Answered

The SQL queries in this project help answer questions such as:

• How many films exist in the dataset?
• What is the average rating by genre?
• Which genres generated the highest revenue?
• Which films achieved the highest ratings?
• What revenue trends exist across genres?

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Project Structure

Film_SQL_Analytics_Project/
│
├── schema/
│   └── 01_create_films_table.sql
│
├── data/
│   └── 01_insert_films.sql
│
└── analysis/
    └── 01_select_and_count.sql

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Example SQL Query

SELECT genre, AVG(rating) AS average_rating
FROM films
GROUP BY genre;

This query calculates the average film rating for each genre, demonstrating SQL aggregation and grouping for analytical reporting.

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Skills Demonstrated

• SQL Query Development
• Data Filtering & Sorting
• SQL Aggregation & Analytical Functions
• GROUP BY & HAVING Analysis
• Relational Database Interaction
• Business Reporting Queries

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Technologies Used

• MySQL
• SQL Workbench

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Author

Tinyiko Patience Mathebula Junior SQL / MySQL Database Administration Portfolio GitHub: https://github.com/Tinyiko-Mathebula GitHub: https://github.com/Tinyiko-Mathebula