Projects
Below are selected projects from my graduate studies at Creighton University. These diverse projects demonstrate the breadth and depth of my data science and data analysis knowledge, skills, and experiences. Enjoy browsing my past projects!
Creighton University
Using predictive analytics techniques, I investigated if the simple data readily available on any weather report (temperature, humidity, date, location) can predict if the total air quality index (AQI) is safe or unsafe. This project used SAS base and SAS Enterprise Miner and advanced statistical techniques to perform data cleaning, analysis, and modeling. I discovered that temperature and humidity impact air quality: colder dry air is more likely to be unsafe, while warm humid air is more likely to be safe.
USCG Recruiting Product Portal
Creighton University
The United States Coast Guard (USCG) Recruiting Command had no tool for tracking inventory of the various products it uses during recruitment activities. This created challenges with disorganized inventory, inefficient ordering practices, insufficient event planning, and lack of product diversity. Our team created a database and front-end web application to organize, view, and update inventory.
Portfolio
Below are links to my portfolio projects. These diverse projects demonstrate the breadth and depth of my data science, analysis, and visualization knowledge, skills, and experiences. Check out my blog for more project examples. Enjoy browsing!
Multiple Sources
I have migrated my portfolio projects into public GitHub repositories. Visit my GitHub profile to view example projects I have done in SQL, Python, and R. The projects featured there are diverse, ranging from school, work, continuing education, continuous learning, and just for fun! Each project includes a detailed Read Me that outlines the project, my approach, and my results.
Multiple Sources
This is a collage of my favorite data visualizations I've created through my graduate studies, personal projects, data volunteerism, and career. Some of the visualizations have their details redacted, but I did my best to provide enough content and context so that you can interpret them accurately. Most of the visualizations shared are screenshots, so don't forget to visit my Tableau Public profile where I have many interactive visualizations and dashboards that I can share publicly.
Creighton University
Using predictive analytics techniques, I investigated if the simple data readily available on any weather report (temperature, humidity, date, location) can predict if the total air quality index (AQI) is safe or unsafe. This project used SAS base and SAS Enterprise Miner and advanced statistical techniques to perform data cleaning, analysis, and modeling. I discovered that temperature and humidity impact air quality: colder dry air is more likely to be unsafe, while warm humid air is more likely to be safe.
