Projects
Real-world analytics case studies focused on data quality, governance, and insights.

Uncover Patterns and Insights of COVID-19 Testing Data

Database Source: BDA500 Class Course

👉 See Full Project ➡️ Links to GitHub

This is GitHub README

👉 See Sample Dataset ➡️ Links to GitHub

➡️ This is GitHub README

👉 View Dashboard ➡️ Links to Excel File

➡️ This is GitHub README

Projects

Project 01: EDA – COVID-19 Testing Data (Excel)

Tools: Excel | Data Cleaning | Dashboard

Database: BDA500 Class Course

Objective:

Uncover patterns and insights in COVID-19 testing data.

Approach:

Cleaned dataset and handled missing values/outliers.
Converted numerical values into categorical data for symptom & demographic analysis.
Created charts: stacked column, line, bar, and scatterplots.

Outcome:

Developed an interactive Excel dashboard with a timeline and slicers.
Delivered actionable insights on symptom trends and testing patterns.

Exploring Patient Demographics and Test Results for Predictive Insights

Database Source: kaggle.com

👉 See Full Project ➡️ Links to GitHub

This is GitHub README

👉 See R Script ➡️ Links to GitHub

➡️ This is GitHub README

👉 View Dashboard ➡️ Links to R Studio File

➡️ This is GitHub README

Project 02: Healthcare Data Analysis Using R Studio

Exploring Patient Demographics and Test Results for Predictive Insights

Overview:

Analyzed a healthcare dataset in R Studio to uncover patterns in patient demographics and test results, setting the stage for predictive analytics in healthcare.

Data Preparation & Cleaning:

Verified dataset integrity; no missing values were present.
Structured demographic and test result variables for analysis.

Analysis & Visualization:

Used descriptive statistics and histograms to examine age distribution and correlations with test results.
Created a heatmap to explore relationships among key health metrics.
Developed pie charts to summarize the distribution of medical conditions across patient populations.

Interactive Dashboard / Outputs:

Compiled visualizations into a coherent, exploratory view of patient demographics and outcomes.
Provided insights to inform predictive modeling and healthcare decision-making.

Tools Used:

R Studio, ggplot2, dplyr, tidyverse

Key Takeaways:

Identified trends between patient age and test outcomes.
Visualized correlations between health metrics to guide further predictive analysis.
Demonstrated the power of R for exploratory data analysis in healthcare datasets.

Unveiling Healthcare Data Exploration with PostgreSQL

Database Source: kaggle.com

👉 See Code Project ➡️ Links to GitHub

This is GitHub README

👉 See PostgreSQL Full Project

➡️ Links to GitHub

➡️ This is GitHub README

👉 View Dashboard ➡️ Links to PostgreSQL File

➡️ This is GitHub README

Project 03: Healthcare Data Analysis Using PostgreSQL

Optimizing Database Performance and Extracting Insights from Healthcare Data

Overview:

Analyzed a comprehensive healthcare dataset using PostgreSQL to improve data handling efficiency and extract actionable insights for healthcare operations and decision-making.

Data Preparation & Management:

Imported and structured the dataset into PostgreSQL tables.
Applied SQL operations for data aggregation, filtering, sorting, and joins.
Created views and employed CTEs (Common Table Expressions) for complex query optimization.

Analysis & Insights:

Performed statistical analysis to assess patient outcomes and healthcare utilization.
Evaluated insurance provider data to identify trends and cost implications.
Analyzed room utilization and doctor performance metrics for operational efficiency.

Tools Used:

PostgreSQL, pgAdmin, SQL

Key Takeaways:

Improved database query performance and efficiency.
Identified actionable insights in patient outcomes, provider performance, and room utilization.
Demonstrated advanced SQL skills for data analysis, reporting, and database management in healthcare contexts.