Hanna Lee- Data Storyteller and Analyst

Hanna Lee

Data Storyteller and Analyst

Welcome to Hanna Lee’s e-portfolio! Take a look at how I utilized Power Query, R, SQL, Power BI, Tableau, Qualtrics, and Canva to clean the data, find stories in the dataset, and visualize findings.

I also developed an AI-powered GPT quiz tool that simulates real-world data scenarios—applying data modeling, relational schema design, and adaptive learning techniques to support others in building their data skills.

Higher Ed Data Analysis Quiz GPT

Built an AI-powered quiz tool that simulates realistic data analysis tasks using relational datasets.

Key Skills Highlighted:

Data Modeling: Designed and visualized a normalized relational data schema with 8 interlinked tables to mirror real-world institutional data environments.
Scenario Design: Crafted applied use cases for SQL, R, Python, and Excel functions based on institutional research and student data workflows.
Adaptive Learning Design: Implemented a retry-loop logic and follow-up questioning based on learner inputs—mimicking the scaffolding process used in data education.
AI-Powered EdTech: Leveraged large language models to build personalized, self-paced learning tools for emerging data professionals.

SUNY enrollment reports using Power Query + API

Click here and then “Learn more about how to get datasets using API” to learn more about how I fetched the data from data.ny.gov using API.

Data visualization examples using Tableau

Data source: Slate CRM
Data size: About 107K rows:
- The total number of rows of undergraduate application data: 77K
- The total number of rows of graduate application data: 30K
Data analysis tool: Tableau Prep Builder to clean and profile data
Data visualization tool: Tableau

All Historical enrollment report examples The query pipeline

*Note: detailed data are blurred.

Fetch API data using R and visualize in Power BI

Research question: How strongly is the retention rate associated with the completion rate across different racial/ethnic groups in higher education, and how does this relationship vary by institutional type (4-year institutions vs. less than 4-year institutions)?
Model: Linear regression
Data source: College Scorecard API
Factors:
Independent factors (X): retention_rate, race
Dependent factor (Y): completion_rate
Additional factors: institution_type (4 years, less than 4 years)
Language: R

Click here to check out the summary of findings and takeaways for college professionals.

Qualtrics dashboard examples

Designed a Qualtrics survey to assess the sense of belonging among international students at Washington University at St. Louis and received 103 responses. Approved sharing the findings, and some survey questions are blurred.

Infographics using Canva

Building Slate queries with SQL

Click here and go to the tab “For advanced users” to learn how I used various SQL commands to customize fields to build numerous Slate queries and reports.