# 🎬 Netflix Analysis & BI Project
An *end-to-end Business Intelligence project* analyzing Netflix content using *Python, **MySQL, **Power BI, and **Azurite* (Azure Storage Emulator). This project demonstrates *real-world BI workflows* including *data pipelines, forecasting with ML, cloud simulation, and dynamic dashboards*.
## ✅ Project Highlights
✔ End-to-end pipeline: Data generation → ETL → Cloud storage → Visualization
✔ *Forecasting: Predict future Netflix content trends using **Linear Regression (scikit-learn)*
✔ *Cloud Simulation*: Azurite for Azure Blob Storage emulation
✔ *Dynamic Dashboard*: Power BI connected to MySQL for live insights
✔ *Professional Documentation*: Includes PDF report and SQL scripts
## 🛠 Tech Stack
- *Python*: Data generation, ETL, ML forecasting
- *Azurite*: Cloud storage simulation
- *Power BI*: Interactive dashboards
- *MySQL*: Database storage & analytics
- *scikit-learn*: Linear Regression for forecasting
## 🔄 Workflow Architecture
## 🔄 Workflow Architecture
1. *Data Generation & Preprocessing (Python)*
- Created Netflix dataset using Python (with optional Faker for synthetic data).
- Cleaned and formatted the data for BI processing.
2. *Machine Learning Forecasting*
- Applied Linear Regression (scikit-learn) to forecast Netflix content trends.
- Generated forecast_dataset.csv for future predictions.
3. *Data Export & Storage*
- Saved datasets (netflix_dataset.csv & forecast_dataset.csv) locally.
- Uploaded datasets to *Azurite* (Azure Blob Storage Emulator) for cloud simulation.
4. *Static Dashboard in Power BI*
- Imported CSV files into Power BI to create an interactive static dashboard.
5. *Database Integration (MySQL)*
- Designed schema and tables.
- Executed queries from sql/netflixqueries.sql to analyze data.
6. *Dynamic Dashboard in Power BI*
- Connected Power BI to *MySQL* for real-time data analysis.
- Configured *Data Source Settings* to show live connection.
7. *Documentation*
- Created a detailed PDF report (Netflix_Project_Report.pdf) summarizing:
- Architecture
- Insights
- Visualizations
** Folder Structure**
netflix-bi-project/ ├── scripts/netflix_etl.py ├── data/netflix_dataset.csv ├── forecast/forecast_dataset.csv ├── sql/netflixqueries.sql ├── powerbi/netflix_dashboard.pbix ├── docs/Netflix_Project_Report.pdf ├── docs/dashboard_screenshot.png ├── requirements.txt └── README.md
***** How To Run****
git clone https://github.com//netflix-bi-project.git cd netflix-bi-project
pip install -r requirements.txt
python scripts/netflix_etl.py
This will generate: • data/netflix_dataset.csv • forecast/forecast_dataset.csv
*** Note*** (If you already have the datasets, you can skip Steps 3 & 4 and directly explore the dashboard.)
Tanmay Sharma
Data Analyst | BI Developer | Python & SQL Enthusiast
📫 Connect with me: LinkedIn | GitHub