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Power BI Healthcare Dashboard Project | Smoking Health Risk Analysis As part of my continued development in Healthcare Data Analytics and Business Intelligence. Problem Statement Smoking data becomes more useful when healthcare professionals can easily connect smoking behavior with demographic and clinical risk factors. However, reviewing patient-level records manually may make it difficult to quickly identify: • The proportion of current, former and non-smokers • Differences in smoking patterns by gender and age group • Smoking duration and average daily cigarette intake • Possible relationships between smoking, cholesterol and hypertension risk • The number of patients showing signs of organ damage Project Objective The objective was to recreate an interactive dashboard that transforms patient smoking and health data into a clear visual report for faster analysis and informed healthcare decision-making. Dashboard Highlights The dashboard provides: ✅ Total patient population and summary health indicators ✅ Average patient age and Body Mass Index ✅ Percentage distribution of smoking status ✅ Smoking-status comparison by gender ✅ Smoking duration and daily cigarette intake across age groups ✅ Cholesterol and hypertension risk classifications ✅ Interactive navigation between healthy and damaged-patient views ✅ Organ-specific analysis for the heart, kidneys, liver and other body systems Key Observations The dashboard analysed 336 patients, with an average age of approximately 53.7 years and an average BMI of 30.0. • 40.18% of the patients had never smoked • 30.95% were current smokers • 28.87% were former smokers • Smoking behavior varied across gender and age groups • Cholesterol and hypertension risk levels also differed across the age categories These insights can help healthcare professionals identify higher-risk patient groups and support targeted screening, preventive education and smoking-cessation programmes. Skills Strengthened Through this replication project, I strengthened my practical understanding of: • Healthcare data interpretation • Data cleaning and transformation • Data modelling • Interactive dashboard design • Visual storytelling and report navigation #PowerBI #HealthcareAnalytics  #HealthcareData #DataAnalytics #BusinessIntelligence #DataVisualization #HealthInformatics  #PortfolioProject
Power BI Healthcare Dashboard Project | Smoking Health Risk Analysis As part of my continued development in Healthcare Data Analytics and Business Intelligence. Problem Statement Smoking data becomes more useful when healthcare professionals can easily connect smoking behavior with demographic and clinical risk factors. However, reviewing patient-level records manually may make it difficult to quickly identify: • The proportion of current, former and non-smokers • Differences in smoking patterns by gender and age group • Smoking duration and average daily cigarette intake • Possible relationships between smoking, cholesterol and hypertension risk • The number of patients showing signs of organ damage Project Objective The objective was to recreate an interactive dashboard that transforms patient smoking and health data into a clear visual report for faster analysis and informed healthcare decision-making. Dashboard Highlights The dashboard provides: ✅ Total patient population and summary health indicators ✅ Average patient age and Body Mass Index ✅ Percentage distribution of smoking status ✅ Smoking-status comparison by gender ✅ Smoking duration and daily cigarette intake across age groups ✅ Cholesterol and hypertension risk classifications ✅ Interactive navigation between healthy and damaged-patient views ✅ Organ-specific analysis for the heart, kidneys, liver and other body systems Key Observations The dashboard analysed 336 patients, with an average age of approximately 53.7 years and an average BMI of 30.0. • 40.18% of the patients had never smoked • 30.95% were current smokers • 28.87% were former smokers • Smoking behavior varied across gender and age groups • Cholesterol and hypertension risk levels also differed across the age categories These insights can help healthcare professionals identify higher-risk patient groups and support targeted screening, preventive education and smoking-cessation programmes. Skills Strengthened Through this replication project, I strengthened my practical understanding of: • Healthcare data interpretation • Data cleaning and transformation • Data modelling • Interactive dashboard design • Visual storytelling and report navigation #PowerBI #HealthcareAnalytics #HealthcareData #DataAnalytics #BusinessIntelligence #DataVisualization #HealthInformatics #PortfolioProject

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