I have a background in Environmental Engineering and am currently building my career in data analytics. I believe that good data leads to better decisions.
Through my experience in project-based work, I have been involved in data-related tasks such as baseline assessment and verification, which further strengthened my interest in working with data.
Python | Power BI | Streamlit
An end-to-end data analysis project exploring bike-sharing demand patterns in Seoul. This study examines how time, weather conditions, seasons, and holidays influence rental behavior, with the objective of supporting operational planning and promotional strategies.
Key outcomes include peak-hour demand identification, weekday versus holiday behavior analysis, and statistically validated insights using A/B testing.
The results are translated into actionable recommendations to improve bike availability and user experience.
SQL | Python | Github | Streamlit
An end-to-end analytics project using TheLook dataset (a fictitious eCommerce clothing site) to evaluate revenue growth, customer value, and product returns.
This analysis translates raw normalized tables into a clean analytics layer via SQL, then validates data quality and derives KPI metrics in Python.
Key outcomes include monthly revenue trend + MoM growth monitoring, return rate diagnostics by category/brand, and customer value segmentation (RFM) to support commercial and operational decision-making.
The insights are packaged into an interactive Streamlit dashboard to enable quick KPI monitoring and drill-down analysis for business stakeholders.
The following case study demonstrate analitical capability, insight generation, and data storytelling.
