Welcome to the **Gym Members Analysis ** project! This repository focuses on analyzing gym member data to uncover actionable insights that can help improve member engagement, optimize workout programs, and predict churn risks. By exploring key metrics and trends, this project demonstrates the SQL queries I can write to solve real-world problems and extract meaningful insights.
- Analysis of member demographics: Age, gender, and membership patterns.
- Evaluation of workout habits: Frequency, session durations, and workout types.
- Insights into calorie burn performance: High-efficiency workouts and trends.
- Churn risk assessment: Identification of members at high risk of churn.
- Breakdown of member segmentation: Experience levels, workout frequency, and preferences.
- Comprehensive SQL-based analysis: Queries designed to uncover trends and solve business challenges.
- Demographic analysis: Age and gender breakdowns, trends by membership type.
- Workout performance trends: Average calorie burn rates, session durations, and engagement levels.
- Risk profiling: Churn prediction based on workout frequency and calorie performance.
This project aims to:
- Showcase my SQL skills by analyzing a real-world dataset.
- Demonstrate data preprocessing, wrangling, and analysis using SQL queries.
- Extract actionable insights about gym member behavior and workout patterns.
- Solve practical business challenges, such as identifying churn risks and optimizing workout programs.
- Fitness Centers: Gain deeper insights into member behavior to improve retention strategies.
- Trainers: Optimize workout plans based on efficiency and member preferences.
- Management: Identify underutilized programs and improve operational efficiency.
- Showcase: Demonstrates my ability to analyze data and generate meaningful insights using SQL.
data-set/: Raw dataset and processed files used in the analysis.gym_members_exercise_tracking.csv: Source dataset from Kaggle.
sql queries/: SQL scripts for data cleaning, wrangling, and analysis.results sql.sql: Contains all SQL queries used to derive insights.
Problem Statement/: Details the challenges and goals of the analysis.-
data-set/: Explaines the solutions for problem statement.
README.md: Project overview and documentation (this file).
- SQL: Data preprocessing, cleaning, wrangling, and analysis.
- Kaggle Dataset: Gym Members Exercise Dataset.
Thank you for visiting this project! If you have any questions, suggestions, or just want to connect, feel free to reach out:
- GitHub: Your GitHub Profile
- LinkedIn: Your LinkedIn Profile
- Power BI Portfolio: Your Power BI Portfolio – Explore my portfolio showcasing Power BI projects and visualizations.
I appreciate your interest and time spent exploring this project. Your feedback is invaluable to me!