Diabetes Risk Adjustment Analysis

This project delivers a strategic analysis of diabetes-related health data using SQLite within a Python Jupyter Notebook environment, enabling healthcare organizations to uncover actionable insights for improved care coordination, risk documentation, and decision-making. By examining common comorbidities, documentation gaps, and the impact of diabetes severity on patient quality of life, the analysis supports early intervention and integrated chronic disease management. Healthcare teams can leverage these insights to prioritize high-risk patients, enhance coding accuracy, and implement targeted, cost-effective interventions.

Credit Card Fraud Detection

This project focuses on detecting and analyzing credit card fraud using SQL and Python within a Jupyter Notebook environment. It involves loading transaction data into a database, performing exploratory analysis with SQL queries, and visualizing key patterns to understand fraudulent behavior. The project also simulates potential fraud scenarios and tests rule-based detection strategies, highlighting how data-driven methods can enhance fraud prevention and decision-making.

Public Pension Plan Analysis

This project showcases a comprehensive analysis of U.S. public pension plans using SQL and Python, leveraging data from the Public Plans Database (PPD) spanning 2001 to 2017. Through a Jupyter Notebook powered by pandas and SQLAlchemy, it explores funding trends, contribution compliance, and investment performance across state retirement systems. Key steps include data validation, auditing for completeness, ranking states by funding health, and evaluating long-term returns. The project highlights SQL proficiency and data analysis skills while uncovering insights into fiscal sustainability and reporting inconsistencies among public pension plans.

My Guitar Shop practice scripts

This project features a curated set of MySQL practice scripts built around the sample "My Guitar Shop" database. Designed for learning and skill-building, the scripts cover essential SQL concepts such as joins, aggregations, subqueries, and user privilege management. Each script demonstrates practical scenarios like identifying top discounted products, analyzing high-value orders, auditing unused categories, and summarizing purchases by product and category. Ideal for beginners and intermediate learners, the project offers hands-on experience with data analysis, reporting, and database administration in a structured, real-world context.