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README.md.md

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+# 🎬 Data-Driven Movie Studio Strategy
+
+This project explores which types of films perform best at the box office and translates these insights into actionable recommendations for a new movie studio. Our analysis combines data from multiple movie industry sources to guide decisions around genre selection, budgeting, casting, and production planning.
+
+---
+
+## 📌 Project Objective
+
+To help a new movie studio make informed decisions by analyzing historical movie data and identifying:
+- What genres perform best?
+- Which budget ranges yield the highest return?
+- Who are the top-performing directors and writers?
+- What runtime leads to better ratings?
+- How can we balance critical acclaim and popularity?
+
+---
+
+## 📂 Datasets Used
+
+We integrated four key datasets:
+
+- **Box Office Mojo:** Domestic and international gross earnings
+- **IMDB (via SQLite):** Ratings, genres, directors, writers
+- **The Numbers:** Production budgets and profitability
+- **TMDB:** Popularity metrics, vote counts, and language
+
+---
+
+## 🧠 Methodology
+
+Following the CRISP-DM process:
+1. **Business Understanding**
+2. **Data Understanding**
+3. **Data Preparation**
+4. **Exploratory Data Analysis (EDA)**
+5. **Visualization & Insight Generation**
+6. **Strategic Recommendation Development**
+
+---
+
+## 📊 Key Findings
+
+- 🎭 **Top Genres:** War, Musicals, and Animation deliver high ratings and wide appeal
+- 🎬 **Bankable Talent:** Directors like *Amitabh Reza Chowdhury* and *Mahesh Manjrekar* consistently receive strong audience ratings
+- 🕒 **Ideal Runtime:** 90–150 minutes yields higher ratings and better viewer engagement
+- 💰 **Best ROI:** Mid-range budgets ($5M–$50M) balance risk and profitability
+
+---
+
+## ✅ Final Recommendations
+
+- Focus on genres with strong critical and global appeal
+- Partner with high-performing, reputable directors and writers
+- Standardize runtimes between 90–150 mins
+- Target mid-range budgets for optimal return
+
+---
+
+## 💼 Contributors
+
+Beth Nyambura, Benson Ouma, Harrison Karime, Rahab Gachie
+
+---
+
+## 📎 Note
+
+This project uses a zipped SQLite database (`im.db.zip`) that is **excluded from the repository** due to size limits.  
+Please place the zip file in the project root folder before running the notebook.
+
+---
+
+## 📁 Repository Structure
+
+```
+.
+├── notebooks/
+│   └── final_analysis.ipynb
+├── data/
+│   └── im.db.zip (excluded from Git)
+├── README.md
+├── .gitignore
+└── Data_Driven_Movie_Strategy_Presentation.pptx
+```
+
+---
+
+## 📊 License
+
+This project is for educational purposes under the Data Science Curriculum (DSC Phase 2).