I am an undergraduate studying Data Science with a keen eye for data quality from my previous role as Junior Data Quality Coordinator. I'm passionate about continuously improving my skills in data analytics and adapting to changes within the data driven world. I'm currently working with technologies like SQL, Python, and Tableau, using data analytics and Generative AI through custom agents with LangGraph to identify actionable insights from raw data.
Data analytics of NBA player performance for the 2024-2025 season using data from the NBA API. The data is processed through an ETL pipeline and stored in a star-schema. A Tableau dashboard presents key player metrics, game statistics, and performance trends. A SQL Agent using LangGraph was created to enhance insights.
Click to learn more!
Investigation of using synthetic data as a privacy-preserving solution for data sharing in cross-functional teams while maintaining data governance. Using GC, CTGAN, and TVAE from the SDV library, we assess data fidelity and privacy through statical comparisons of datasets and privacy metrics across varied simulated dataset conditions.
Click to learn more!
This project aimed to improve on-time graduation rates for business students, who currently take an average of 6.5 years to graduate. Through data analysis and machine learning, it was found that students with multiple concentrations take fewer irrelevant courses, leading to our recommendation of requiring two concentrations for Business graduates.
Click to learn more!
This project analyzed factors influencing hotel booking cancellations, which currently occur at a 40% rate. Through feature engineering and machine learning, we identified key drivers—such as deposit type and special requests—and recommended a partially refundable deposit to improve retention.
Click to learn more!