🏆 Oscar Awards Analysis (1927–2025)

This repository contains a structured SQL analysis of historical Oscar Award nominations and wins, covering nearly a century of cinematic achievements. The project aims to extract key performance metrics, identify trends, and highlight impressive achievements across films and performers.

🌟 Dataset Context

The data covers The Academy Awards (the Oscars), the premier awards for artistic and technical merit in the film industry, presented annually by the Academy of Motion Picture Arts and Sciences (AMPAS).

• Source: The Academy Awards Database via Kaggle: The Oscar Award, 1927–2025
• Original Authors: Raphael Fontes and David Lu!!
• File: data/the_oscar_award.csv

⚙️ Project Requirements and Structure

This analysis is optimized for a modern SQL environment, requiring specific aggregate functions.

• SQL Dialect: PostgreSQL (due to the use of FILTER and ARRAY_AGG).
• Repository Structure:
  • schema.sql: Contains the CREATE TABLE statement for the oscars table.
  • queries.sql: Contains the 10 analytical SQL queries.
  • data/: Stores the raw data file.
  • findings.md: The final report. Summarizes the key findings, conclusions, and metrics derived from the executed SQL queries.

🚀 SQL Analysis: Key Objectives

The file queries.sql is structured into 10 sections, focusing on three main areas:

Films & Performance

1. Identify films with the highest number of Oscar wins.
2. Find film hit rate (wins/nominations).
3. Films that won all nominations they had in a year.
4. 'Big Five' films; films that won in 5 major categories.

Performers & Individuals

5. Find Top-10 performers with the most Oscar wins (Acting categories only).
6. Find performers with the highest number of nominations but no Oscar wins (Acting categories only).
7. Count longest wait to first acting Oscar win.
8. Top-10 directors with the most wins.
9. People who have Oscar wins across $\ge2$ competitive categories (e.g., ACTING, MUSIC, DIRECTING).

Ceremony & Trends

10. Number of different winning films at the ceremony.

🛠️ Usage Instructions

To replicate this analysis:

1. Save this repository locally.
2. Create the Table: Run the commands in schema.sql against your PostgreSQL database.
3. Load Data: Import the the_oscar_award.csv file from the data/ folder into the newly created oscars table.
4. Run Analysis: Execute the queries found in the queries.sql file.

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License: This project is under the MIT License.