Data Analyst Portfolio - Supoj Xu

Welcome to my portfolio!

My name is Sean, I am a data analyst with experience using various data tools to clean, analyze, and visualize data to empower decision making and drive changes. I am proficient in SQL, Excel, Tableau, and Python, and have a good understanding of data analytics techniques including, but not limited to, data preparation, data wrangling, statistical analysis, charts design, dashboard building, process documenting, and data storytelling.

In this portfolio, I have included data projects that showcase my technical skills as well as analytical capability. You will find documents, workbooks, presentation slides, and dashboards created with SQL, Tableau, Excel, Jupyter Notebook, RStudio, and PowerPoint. These projects demonstrate my ability to organize, analyze, and present data in a clear and visually appealing way, making it easy for anyone to understand and make informed decisions.

* Tableau * Airline Loyalty Campaign and Churn Analysis * Executive Business Sales Dashboard * Nobel Prize Laureates Data Visualization * Python * Customer Segmentation with RFM Model * SQL * Chicago City 311 Service Analysis * Excel * Airbnb Bangkok Listings and Price Analysis * RStudio * Fitness Tracker Data Exploration

Certificates

Education

Projects

In this section you can find short summary of the listed projects for quick comprehension. For more details, please check out the documents in each respective project folder.

Airline Loyalty Campaign and Churn Analysis

For this project, I analyzed loyalty program data including program enrollment, cancellation details, customer information, and flight activities. My objectives were to help the airline capture the impact of their recent promotional campaign, find patterns among churn members, and recommend appropriate actions. After exploration and analysis, I visualized important findings about the impact of the campaign, the potential problem, and churn patterns with appropriate charts and design methods, leveraging pre-attentive attributes for effective visuals. In the end, I presented the findings and suggestions in a series of Tableau story points with annotations.

The skills showcased in this project are data connections, calculated fields, sets, groups, binning, filters, dashboard, story, and presentation.

Customer Segmentation with RFM Model

For this project, I analyzed retail transactions data and classified customers into distinct groups by using RFM model and quantile scoring method. The objective was to help the business gain insights and develop effective engagement strategies based on customer behaviors. In the end, I created two tables describing group charateristics and sharing recommended marketing strategies.

The skills showcased in this project are Python libraries (Numpy, Pandas, Matplotlib, Seaborn), for loop, def statement, branching, data slicing, data merging, nulls & duplicates handling, RFM analysis, quantile scoring, outliers removal, and subplot visualization.

Chicago City 311 Service Analysis

For this project, I conducted an analysis on 2.8 million rows of data using a combination of SQL and Excel. The goal was to help a public agency in Chicago improve ticket resolution time by understanding where they should focus their resources on. After exploring the data, I created a priority quadrant based on two selected metrics, plotted the data against the quadrant, cross-validated the findings with data from New York City, and deep dived to find patterns in location fields. In the end, I shared the key insights, suggestions, and remarks in a presentation.

The skills showcased in this project are data querying, data validation, JOINs & UNION clauses, aggregation, datetime conversion, filtering, subqueries, CTEs, conditions, PivotTables, Pivot Charts, and presentation.

Airbnb Bangkok Listings and Price Analysis

For this project, I cleaned and analyzed data which was scraped directly from Airbnb platform. The data contained over 70 columns and had many formatting issues to be addressed. The main objective was to find any useful insights that can help first-time Airbnb hosts in Bangkok determine best pricing and listing practices to maximize their long-term revenue based on a variety of dimensions such as room type, location, number of bedrooms, minimum nights, etc. In the end, I presented relevant findings in an easy to understand presentation format.

The skills showcased in this project are data cleaning (e.g.: nulls & duplicates handling, data correction, outliers detection), string extraction, XLOOKUP referencing, categorizing, descriptive statistics, correlation, PivotTables, conditional formating, process documenting, charts building, and presentation.

Fitness Tracker Data Exploration

In this project, I conducted a data exploration on Fitbit fitness tracker data. There were 18 CSV files which I narrowed down to 4 core CSV files containing fitness data of users such as steps, calories loss, minutes sleep, etc. The main objective was to identify trends and insights regarding user health, behavior, and smart device usage that could be useful for health tech companies to improve their product and service offerings. I divided this project into 4 phases and explained each step along with the results in markdown format.

The skills showcased in this project are data importing, assaying, data cleaning (e.g.: duplicates handling, reformatting columns), data merging, descriptive statistics, aggregating and manipulating fields, data visualization, reporting.