Data Science / Analytics Projects
1. Database development for the College of Nursing
Skills Used: Microsoft Access, SQL Queries, VBA, Relational Schema
For the University of Iowa's Nursing Residency Program, I designed a relational Microsoft Access database that streamlined their data management process. By integrating their customer and sales information, as well as creating custom forms and automated reports, I reduced manual labor by over 50%. The database allows the company to track customers, manage invoicing, and gain valuable insights through easy-to-use reports. With the ability to search and edit customer data and create professional invoices, this database provides a comprehensive solution for the company's data management.
2. Sentiment Analysis of The Hill: Exploring Political Sentiment across Topic Categories
Skills Used: Python, Machine Learning
This sentiment analysis project focused on analyzing sentiment in articles scraped from The Hill, a prominent news outlet covering politics and government affairs in the United States. I explored how sentiment varies across different topic categories such as News, Policy, Business, Opinion, Events, and Jobs. Through web scraping and data analysis, I aimed to provide insights into the political landscape and contribute to the field of text analytics. The repository contains code, documentation, and findings, inviting others to learn and contribute to our work in sentiment analysis.
3. Credit Card Churn Rate Predictive Modeling
Skills Used: R, Machine Learning, RStudio
This project used supervised machine learning to analyze credit card company data
and build a model to predict customer churn. Exploratory analysis revealed that
customers with lower transaction numbers and amounts, lower revolving balances,
and fewer total products were more likely to churn.
The best model, a gradient boosting model, had an AUC of .9911 and an average error rate of 7.6%. The model
had a precision of 96% and a recall of 85.7%. The conclusion and recommendations
suggest that the company should offer incentives such as cashback rewards and travel
amenities to retain customers.
4. Best Flight Analysis: Chicago O' Hare Airport
Skills Used: SQL, Oracle Apex
This project aims to ease the airport experience for travelers by providing statistical data to help choose an airline and day to fly from Chicago O'Hare International Airport. The project uses data from the 2015 Kaggle data on Commercial Air Flight Delays, which includes over 5 million commercial flights. The report provides an in-depth analysis of the data, and frequent fliers of O'Hare can benefit from it. The website provides screenshots of the final report.
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