Portfolio - Data Analytics
Data analyst with a focus on healthcare analytics and operational insights. I build end-to-end projects from raw data to dashboards using Python, SQL, and BI tools to answer questions that drive decisions.
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Interactive dashboard analyzing readmission patterns across 300 patients and 5 diagnoses. Heart Failure patients showed a 39% readmission rate, nearly 6x higher than surgical cases. Built with DAX measures and interactive slicers filtering by insurance type, department, and gender.
Python engineered a weighted attrition risk score per employee across 8 factors. Power BI dashboard built on the enriched dataset identifies Sales and Marketing at 28% attrition, 8 points above the 15% target. Features a scatter plot, department treemap, gauge, and interactive slicers.
Interactive Tableau dashboard analyzing 2019 World Happiness Report data across 156 countries. Choropleth world map, GDP vs happiness scatter plot with trend line, top 20 countries bar chart, and happiness factors comparison. Live and interactive on Tableau Public.
Interactive Looker Studio dashboard analyzing 300-patient hospital readmission dataset. Features scorecards, bar charts by diagnosis and insurance type, pie chart by discharge destination, and a live dropdown filter. Connects directly to Google Sheets as the data source.
Advanced spreadsheet analysis using 3 pivot tables, COUNTIFS, COUNTIF, INDEX/MATCH, and calculated readmission rates by diagnosis and insurance type. Dashboard tab pulls live KPIs from formula sheet. Heart Failure readmission rate 39.29% vs 7.04% for Hip/Knee Replacement.
6 queries across 4 real PostgreSQL databases demonstrating CTEs, window functions, conditional aggregation, subqueries, and date functions. Key finding: 210 whales generate 52% of game revenue despite being 9% of paying users. NYC Instacart issue rate 3x higher than Chicago.
End-to-end web analytics project exploring Grammy Awards data. Applies data wrangling, exploratory analysis, and visualization to uncover audience and engagement patterns.
Hands-on Python lab exercises covering data manipulation, functions, and analysis workflows. Demonstrates foundational programming competency applied to real datasets.
9-part project series covering progressively advanced analytics techniques from data cleaning and aggregation through statistical analysis and visualization. Datasets include Dunder Mifflin sales, Nike/Adidas, and Lyft bike share data.