Power BI Health Data Analysis

This project presents a comprehensive Power BI report for analyzing health-related datasets, focusing on environmental impacts on mental and physical well-being. The report is developed using Microsoft Power BI and covers multiple dimensions of urban health, including air pollution, noise, stress levels, sleep quality, and healthcare records.

📊 Project Overview

The analysis is based on two primary datasets:

1. Air Pollution and Mental Health
   Provided by the CitieS-Health project and collected in Barcelona, Spain. It investigates how air pollution and environmental factors (e.g., NO₂ levels, noise, green space exposure) influence mental health and well-being. It includes self-reported data such as stress levels, sleep quality, and cognitive test results (e.g., Stroop test).

2. Healthcare Dataset
   A hospital dataset covering U.S. patients from 2019 to 2024. It includes information about medical conditions, hospital admissions, billing, treatments, and outcomes, enabling trend and cost-effectiveness analyses over time.

🛠️ Tools Used

• Microsoft Power BI: For data import, cleaning, modeling, and dashboard/report creation.
• Power Query Editor: For data transformation.
• GeoJSON + Shape Map: For district-level geospatial filtering in Barcelona.

🧹 Data Preparation

• Null value treatment (removal, replacement with mean, etc.)
• Data type conversions
• Redundant or erroneous data elimination
• Feature engineering (new calculated columns such as well-being level, sleep quality groupings, etc.)

🔍 Key Analyses

Air Pollution and Mental Health Dataset

• Correlation between NO₂ levels and well-being, stress, and cognitive performance
• Impact of noise on perceived stress
• Sleep quality versus air quality
• Effect of education level on perceived well-being
• Outdoor activity time vs. exposure to pollution
• Seasonal trends in pollution and temperature
• Gender-based exposure comparisons
• District-specific dashboards (via interactive maps)

Healthcare Dataset

• Patient age vs. recovery time and medical condition
• Admission type analysis
• Clustering of patient profiles
• Blood type distribution and health outcomes

📁 Data Sources

• Air Pollution and Mental Health
• Healthcare Dataset
• Power BI Official Website

📍 Geographic Scope

• Barcelona, Spain (Air pollution dataset)
• United States (Healthcare dataset)

📌 Notable Features

• Interactive filtering by district, gender, or survey date
• Use of geospatial mapping for targeted insights
• Temporal trend analysis for both health and environmental variables
• Dynamic dashboards with slicers and KPIs

📊 Preview

📑 Author

Micol Zazzarini
Developed as part of a Business Intelligence project using Microsoft Power BI.