How I Turned Real-World Problems Into Data Analytics Projects

Finding Analytics in Unexpected Places

When people think about data analytics, they usually picture dashboards, coding, and spreadsheets. That’s definitely part of it, but honestly, my path into analytics started somewhere completely different: working in restaurants.

Over the last few years, I’ve balanced being a full-time college student, working in fine dining, and trying to figure out what I wanted to do professionally. At first, hospitality and analytics felt like two completely separate worlds. One was fast-paced and people-focused, while the other revolved around statistics, programming, and data.

Where the Curiosity Started

But the more I worked in restaurants, the more I started noticing patterns.

I became interested in how things operated behind the scenes — reservations, cancellations, staffing, guest flow, and how even small operational decisions could affect the entire night. I found myself constantly asking questions:

• Why are some nights significantly busier than others?

• Why do cancellations spike on certain days?

• Could staffing schedules be optimized better?

• How can data actually improve operations?

Turning Questions into Projects

That curiosity is what pushed me deeper into analytics.

At High Point University, I started building projects around real-world business problems instead of just classroom examples. One of my favorite projects focused on restaurant reservation analytics using R and Power BI. I analyzed cancellation trends, compared expected vs. actual covers, and built predictive models to better understand guest behavior and operational performance.

Expanding Beyond Restaurant Analytics

From there, I expanded into other projects involving machine learning, statistical analysis, and predictive modeling:

• Predicting workplace safety incidents using Random Forest models in R

• Analyzing Olympic athlete performance data in Python

• Conducting healthcare hypothesis testing and statistical analysis

• Building dashboards and visualizations for operational reporting

  
  

Why I Enjoy Analytics

What I enjoy most about analytics is that it has real impact.

Good analytics is not just about making charts look nice — it’s about helping people make better decisions. Whether it’s improving restaurant operations, identifying safety risks, or uncovering trends in large datasets, I like being able to take raw information and turn it into something meaningful.

Looking Ahead

As I graduate from High Point University and prepare to move to New York City, I’m excited to continue growing both professionally and personally. I’m still learning every day, but that’s one of the things I love most about analytics — there’s always something new to figure out.

This portfolio is a collection of the projects and experiences that have shaped my journey so far, and I’m excited to keep building on it.

Thanks for reading.