📊 Nifty100 Analytics Project

📌 Project Overview

Nifty100 Analytics is a data analytics project that processes and analyzes Nifty100 company financial data.

The project uses Python, Pandas, SQLite, and SQL to build an ETL pipeline that loads, validates, stores, and analyzes financial datasets.

---

🎯 Project Objectives

• Collect Nifty100 company financial datasets
• Clean and validate raw data
• Create structured database tables
• Load data using ETL pipeline
• Perform SQL-based analysis
• Generate quality reports

---

🛠️ Technologies Used

• Python
• Pandas
• SQLite
• SQL
• Git & GitHub
• Excel Dataset Processing

---

📂 Project Structure

Nifty100_Analytics
│
├── data/
│   └── raw/
│       └── Financial datasets (.xlsx)
│
├── db/
│   └── SQLite database
│
├── notebooks/
│   └── SQL analysis queries
│
├── output/
│   └── Validation reports
│
├── src/
│   └── etl/
│       ├── loader.py
│       └── normalizer.py
│
├── tests/
│   └── etl/
│       └── Data validation tests
│
├── create_tables.py
├── review_data.py
└── README.md

---

📅 Project Progress

Day 1: Environment Setup

• Created project structure
• Setup Python environment

Day 3: Data Validation

• Implemented schema validation
• Added 16 Data Quality rules

Day 4: Database Creation

• Created SQLite database
• Added primary key and foreign key constraints

Day 5: Data Loading

• Loaded 12 Nifty100 datasets
• Completed ETL data loading process

Day 6: Data Quality Review

• Verified database tables
• Checked loaded records
• Performed manual data quality review

Day 7: Analysis & Review

• Created SQL exploratory queries
• Reviewed complete project workflow

---

📊 Datasets Used

• Companies
• Stock Prices
• Market Capitalization
• Financial Ratios
• Balance Sheet
• Profit & Loss
• Cash Flow
• Sectors
• Peer Groups
• Documents
• Pros & Cons
• Analysis Data

---

🚀 How to Run Project

Clone repository:

git clone <your-github-link>

Install requirements:

pip install pandas openpyxl

Create database:

python create_tables.py

Load data:

python src/etl/loader.py

Review data:

python review_data.py

---

👩‍💻 Author

Ungarala Ramya

B.Tech Computer Science Engineering

---

⭐ Project Status

Completed ✅