DIVVY Bike Data Analysis
To analyze urban mobility patterns, I worked with a 5.63 million record dataset from Divvy’s bike-sharing system.
The goal was to uncover usage trends based on rider type, bike type, time, and location.
I built an interactive Power BI dashboard that segmented rides by subscriber vs. casual users, bike types,
and visualized average ride durations and ride counts across days and months.
I also integrated geospatial maps and time series filters for dynamic exploration, and included a full data
grid for detailed review. This solution helped highlight key user behaviors and informed data-driven
decisions around fleet and station management.
CVS Clinics Analysis
To support operational insights across retail healthcare, I analyzed a comprehensive dataset of CVS Minute Clinics across the U.S. The objective was to identify patterns in clinic accessibility, 24-hour pharmacy services, and optical service availability across various store types. I built an interactive dashboard that mapped clinics by state, city, and postal code, categorized them by store type (CVS, Target, Navarro, etc.), and included filters for store time zones and locations. I also integrated a data grid for detailed record-level analysis. This dashboard enabled stakeholders to pinpoint service coverage gaps and better understand regional healthcare access.
Data Profession Survey
I analyzed the Kaggle survey dataset to uncover patterns among thousands of data professionals across the globe. Using Power BI, I designed an interactive dashboard that displays salary trends, tool preferences, country-based breakdowns, and role comparisons. The visualizations help both aspiring data professionals and hiring managers understand the current state of the industry. This project not only highlights technical proficiency in Power BI but also the ability to design a story-driven, user-friendly report from raw survey data.
Seattle Airbnb Data
To analyze short-term rental dynamics in Seattle, I used Tableau to create a dashboard based on Airbnb listings data. I cleaned and joined multiple datasets, then designed visualizations that broke down price, availability, and neighborhood saturation. Users can interact with the dashboard to identify optimal pricing strategies, seasonal availability, and high-performing locations. This project demonstrates my ability to connect raw geospatial data to business-relevant insights, making it especially useful for hosts, investors, or urban policy planners.
Covid-19 Impact Analysis
During the global health crisis, I took initiative to analyze the COVID-19 pandemic’s worldwide impact using real-time datasets.
I used SQL to clean, transform, and calculate daily cases, deaths, and vaccination metrics using CTEs and window functions.
I then visualized this using Tableau, building a dynamic dashboard that captured global disparities and trends.
This allowed users to clearly track surges, vaccination rollouts, and regional patterns, providing both governments and individuals with a visual narrative of the pandemic's evolution.
Bike Sales Dashboard
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To help a retail client understand their bike sales performance, I built a dynamic dashboard in Excel using pivot tables, slicers, and conditional formatting. I analyzed customer demographics such as age, gender, and income level and correlated them with purchasing patterns. The dashboard provided instant insights into which customer types and regions drove the most sales, allowing for smarter marketing segmentation. The result was a visual tool that enabled faster, data-driven sales decisions without the need for technical tools.