A24 Film Database (SQL)
The Situation
This project began as a structured exploration of A24’s film catalog through database design. The goal was to create a relational system that could document and organize a large set of film-related variables in a way that supported both technical practice and analytical use. Rather than working with a flat dataset, I wanted to build a database that reflected how film information is actually structured: across titles, people, languages, platforms, budgets, awards, and ratings.
The database ultimately documented more than 135 A24 films, with over 20 attributes per title. The project functioned as both a technical exercise in SQL and data modeling, and as a way to examine patterns in film production, distribution, and audience reception through a structured dataset.
The Approach
I designed the project as a relational database rather than a single-table archive. The first step was to define the main entities and the relationships between them, then build a schema that balanced normalization with practical retrieval needs. Seven interconnected tables were created to represent key dimensions of the dataset, including movie details, languages, awards, crew, ratings, streaming platforms, and budgets.
To maintain consistency, I established primary and foreign key relationships and applied constraints where needed to protect data integrity. Performance was also part of the design process, so indexing and subqueries were used to support more efficient querying across larger combinations of data.
Once the schema was in place, I developed a broad set of SQL queries to analyze different aspects of the catalog, including genre distribution, runtime variation, IMDb ratings, director counts, filming locations, and release-related patterns. I also created stored procedures and views to simplify repeated retrieval tasks and make more complex datasets easier to work with. The project concluded with structured export in JSON format and dashboard development in Tableau for visual analysis.
Key Deliverables
Relational SQL database covering 135+ A24 films
Seven interconnected tables for film, crew, awards, language, ratings, streaming, and budget data
Primary and foreign key structure with integrity constraints
Indexing strategy to improve retrieval performance
50+ SQL queries for catalog analysis and comparison
10+ stored procedures for repeated retrieval tasks
Multiple database views for simplified access to complex data relationships
JSON export for structured reuse across applications
Tableau dashboards visualizing budget trends, genre distribution, and audience ratings
The Results
The project produced a structured and scalable SQL database that could support both film analysis and database practice. It demonstrated applied work in relational modeling, normalization, query writing, performance tuning, and data visualization within a single project environment.
From a technical perspective, the database supported reliable storage and retrieval across multiple related entities without collapsing the dataset into a less flexible format. From an analytical perspective, it made it possible to examine recurring patterns across the A24 catalog through query logic and visual reporting.
The project also strengthened my practical understanding of database systems by requiring decisions about schema design, constraints, optimization, and usability, not just data entry. In that sense, it worked as both a research-oriented dataset and a hands-on technical build.
