Interactive Road Accident Analysis Dashboard PROJECT_DESCRIPTION: I'd like an engaging Power BI dashboard created to track road accident key performance indicators such as severity, fatality rate, peak hours, and high-risk zones. Data for the dashboard w
Budget: ₹600 – ₹10,000 INR
Road Accident Analysis Dashboard | Power BI | DAX
• Engineered an interactive Power BI dashboard tracking 5+ accident KPIs (severity, fatality rate, peak hours,
high-risk zones) using DAX measures across a 12-month dataset.
• Reduced insight discovery time by ~40% for stakeholders by replacing static reports with drill-down filters by
location, vehicle type, and accident cause.
• Applied DAX-based time intelligence to compare YoY fatality trends, revealing a 15% increase in night-time
accidents that guided policy recommendations.
AI-Enabled Multi-Disease Detection System | Machine Learning | Python
• Built a multi-label ML classifier detecting Diabetes and Heart Disease with 87%+ accuracy using Logistic
Regression and Random Forest on a 1,000+ patient dataset.
• Reduced false negatives by 18% through feature engineering and threshold tuning — critical for early medical
diagnosis applications.
• Automated the full pipeline: data preprocessing, EDA, model training, and evaluation (Precision, Recall,
ROC-AUC), cutting manual analysis time by 60%.
Swiggy Food Delivery Data Analysis | SQL | Python | Power BI
• Designed a star schema data warehouse with 4 dimension tables and 1 fact table; executed ETL on 50,000+
rows of raw CSV delivery data using SQL.
• Identified top 3 high-revenue cuisines and a 22% pricing gap between premium and budget restaurants
through SQL aggregations and trend analysis.
ANALYSIS OF INDIAN ELECTION DATA | SQL, POSTGRESQL
• Developed and processed a "relational database" to extract data from the election results concerning
constituencies and states Explained Complex SQL queries involving JOINs, CTEs, WINDOW FUNCTIONS,
GROUP BYs, and CASE statements Extracted winning candidates, runner-ups, margins of victory, and trends
of party performance With Visulization
• Engineered an interactive Power BI dashboard tracking 5+ accident KPIs (severity, fatality rate, peak hours,
high-risk zones) using DAX measures across a 12-month dataset.
• Reduced insight discovery time by ~40% for stakeholders by replacing static reports with drill-down filters by
location, vehicle type, and accident cause.
• Applied DAX-based time intelligence to compare YoY fatality trends, revealing a 15% increase in night-time
accidents that guided policy recommendations.
AI-Enabled Multi-Disease Detection System | Machine Learning | Python
• Built a multi-label ML classifier detecting Diabetes and Heart Disease with 87%+ accuracy using Logistic
Regression and Random Forest on a 1,000+ patient dataset.
• Reduced false negatives by 18% through feature engineering and threshold tuning — critical for early medical
diagnosis applications.
• Automated the full pipeline: data preprocessing, EDA, model training, and evaluation (Precision, Recall,
ROC-AUC), cutting manual analysis time by 60%.
Swiggy Food Delivery Data Analysis | SQL | Python | Power BI
• Designed a star schema data warehouse with 4 dimension tables and 1 fact table; executed ETL on 50,000+
rows of raw CSV delivery data using SQL.
• Identified top 3 high-revenue cuisines and a 22% pricing gap between premium and budget restaurants
through SQL aggregations and trend analysis.
ANALYSIS OF INDIAN ELECTION DATA | SQL, POSTGRESQL
• Developed and processed a "relational database" to extract data from the election results concerning
constituencies and states Explained Complex SQL queries involving JOINs, CTEs, WINDOW FUNCTIONS,
GROUP BYs, and CASE statements Extracted winning candidates, runner-ups, margins of victory, and trends
of party performance With Visulization
Related categories:
Python
SQL
Machine Learning (ML)
Data Mining
Data Warehousing
Data Science
Data Analysis
Power BI