#FitTrack_Personal_Health_&_Fitness_Analytics_Project SQL-based Health & Fitness Analytics project using Oracle Database

📊 FitTrack: Personal Health & Fitness Analytics Project A beginner-friendly SQL project that analyzes daily health and fitness data using Oracle Database 21c. This project is designed to strengthen SQL skills while working with realistic health tracking data such as steps, calories, sleep, and water intake.

📌 Objective To create a health analytics system using SQL that helps monitor user fitness trends and generate insights using real-time queries and window functions.

🛠️ Tools & Technologies Database: Oracle Database 21c Express Edition

Language: SQL (Oracle SQL syntax)

Platform: Oracle SQL Developer

📁 Project Structure FitTrack_SQL_Project/ │ ├── SQL_Files/ │ ├── create_tables.sql │ ├── insert_data.sql │ ├── analysis_queries.sql │ ├── Documentation/ │ └── README.md

👥 Dataset Description Custom data for 20 users including:

Personal details (name, gender, age, height, weight)

Daily activity logs (steps, sleep, workout minutes, water intake)

Meal logs (calories, protein, carbs, fat, etc.)

📊 Key Features ✅ Created and linked normalized tables using foreign keys ✅ Inserted realistic dummy data for 20 users ✅ Performed health and fitness analytics using:

JOIN, GROUP BY, HAVING

Aggregate Functions (SUM, AVG, MAX, MIN)

Window Functions (ROW_NUMBER, RANK, AVG OVER)

Subqueries and filters

Weekly trends and leaderboards

Water and calorie tracking

🔍 Sample Analysis Queries Top 5 active users in the last 7 days

Users who consumed more than 2000 calories per day

Moving average of water intake (window function)

Weekly step count leaderboard

Sleep duration vs. workout correlation check

Join-based summaries per user

All queries tested and written specifically for Oracle SQL.

📈 Example Insight "Amit Sharma had the highest average steps in the last 7 days, while Deepa More maintained the most consistent water intake."

📎 How to Run the Project Set up Oracle Database 21c XE

Open Oracle SQL Developer

Run create_tables.sql

Run insert_data.sql

Explore insights using analysis_queries.sql

💡 What I Learned Writing clean and efficient SQL queries

Using JOINs and Window Functions in real-world scenarios

Structuring SQL projects for GitHub

📬 Feedback or Suggestions? Feel free to open an issue or drop suggestions. Contributions are welcome!

🙋 About Me

Hi, I'm Shivani — an aspiring data analyst passionate about using data to uncover meaningful health insights.
This is one of my practical projects to demonstrate my growing SQL skills.

📫 Connect with me on LinkedIn (www.linkedin.com/in/shivani-kodape-b91175308)