Exploring lifestyle and health-related data using PostgreSQL and Power BI to identify trends, patterns, and insights through data visualization and analysis. Includes SQL scripts, Power BI dashboards, and full project documentation.
This project was born out of a curiosity about how everyday lifestyle choices — diet, workout habits, and activity levels — connect to measurable health outcomes like BMI. Using a real-world lifestyle dataset, the goal was to go beyond surface-level averages and identify the outliers: individuals whose patterns stand out and may signal unique habits or potential health risks.
This analysis explores demographic and lifestyle drivers including BMI, age, gender, workout experience, and diet type. Key questions investigated:
- Which demographic groups fall outside healthy BMI ranges?
- Is there a correlation between workout frequency and BMI outliers?
- How does diet type influence health scores across age groups?
Key Finding: Analysis revealed that a significant portion of individuals fell outside healthy BMI ranges, with diet type and workout experience showing the strongest correlations.
- 📁
data/→ raw and cleaned datasets - 📁
sql/→ SQL scripts for queries and transformations - 📁
dashboards/→ Power BI dashboard screenshots - 📁
docs/→ documentation and notes - 📄
README.md
| Tool | Purpose |
|---|---|
| PostgreSQL | Data cleaning, schema alignment, outlier queries |
| Power BI | Interactive dashboards and visual storytelling |
| Excel | Quick checks, formatting, and data validation |
| GitHub | Version control and project sharing |
- Individuals with inconsistent workout schedules showed higher rates of BMI outliers
- Diet type was a stronger predictor of BMI range than age or gender
- Outliers were not evenly distributed — certain age groups showed clustering outside healthy ranges
- Clone the repository:
- Explore the
data/folder for the raw dataset - Review SQL scripts in the
sql/folder - Open Power BI dashboard files in the
dashboards/folder
Junior Data Analyst passionate about using data visualization and analytics to uncover insights that support health-focused and social impact initiatives. Skilled in PostgreSQL, Power BI, and Excel. Open to collaboration and feedback.
🔗 GitHub: github.com/Obiageli-E