IMDB Movies Analysis

Project Overview

This project analyzes IMDB movie data to uncover trends in movie releases, director performance, ratings, revenue, and popularity. The project demonstrates end-to-end data analysis skills, including SQL data cleaning, data transformation, and interactive dashboard creation using Power BI.

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Project Objectives

• Explore and clean raw movie and director datasets.
• Perform SQL queries to extract meaningful insights.
• Join movies and directors tables to create a unified dataset.
• Build an interactive Power BI dashboard to visualize key metrics.
• Present insights through professional slides (PPT).

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Dataset Details

Movies Table

• Columns: id, title, original_title, release_date, budget, revenue, vote_average, vote_count, popularity, director_id, etc.
• Contains movie information including ratings, revenue, and director IDs.

Directors Table

• Columns: id, name, gender, department
• Contains director details linked to movies via director_id.

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Tools & Technologies

• SQL (MySQL Workbench) – Data cleaning, table joins, and analysis queries.
• Power BI – Data transformation, interactive visualizations, and dashboard creation.
• Microsoft PowerPoint – Presentation of insights and final results.
• CSV Export/Import – Smooth data transfer between SQL and Power BI.

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Steps Performed

1. SQL Tasks

• Explored movies and directors tables to understand schema.
• Cleaned invalid and missing values (budget, revenue, ratings).
• Performed joins between movies and directors using director_id.
• Extracted final analysis dataset (imdb_final.csv) for dashboard.

2. Data Cleaning in Power BI

• Corrected data types (dates, numbers).
• Replaced null or missing values with appropriate defaults.
• Trimmed text fields (director names).
• Extracted release_year for trend analysis.

3. Dashboard Creation

• Built interactive Power BI dashboard including:
  • KPIs: Total Movies, Average IMDB Rating, Total Revenue
  • Line Chart: Movies released per year
  • Bar Chart: Top 10 Directors by Movie Count
  • Column Chart: Top Directors by Average Rating
  • Scatter Plot: Popularity vs Rating (optional)
  • Slicers for filtering by Year and Director

4. Presentation

• Prepared PPT slides to summarize the project, methodology, and insights.

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Key Insights

• Directors with the highest movie count can be easily identified.
• Average IMDB ratings vary across directors and genres.
• Trends in movie releases over the years reveal peak production periods.
• Budget vs Revenue analysis highlights top-grossing films.

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Project Outcome

• Cleaned and joined dataset ready for analysis (imdb_final.csv).
• Interactive Power BI dashboard highlighting key metrics and trends.
• Professional slides summarizing the analysis for presentations.
• Demonstrates strong skills in SQL, data cleaning, and visualization.