Why I Started A Ray of Data & What to Expect

Welcome to A Ray of Data. This first post is a little introduction to who I am, how I moved from math teaching into data science, and why I’m documenting my learning journey publicly. My goal is to build a portfolio that shows not just finished projects, but also the process behind them.

Who I Am

My name is Rachael, but I go by Ray. I’m an aspiring data professional, a former high school math teacher, and someone who has always loved learning, problem solving, and helping ideas make sense. Before moving into data science, I taught Algebra II and Geometry, which shaped how I think about patterns, clear communication, and breaking complex topics into something more approachable.

I grew up in rural Texas and took a nontraditional path into my career. After high school, I went straight into the workforce as a customer service representative, where I started building communication, leadership, and problem-solving skills in early adulthood. With encouragement from my husband, I returned to school to pursue my love of mathematics.

I earned my B.S. in Mathematics from the University of Texas at Austin in 2015. In 2019, I moved to Michigan to be closer to family, and I later earned a B.S. in Data Science from Central Michigan University in 2026. At CMU, I built skills in Python, R, SQL, data visualization, and machine learning.

Outside of data science, I enjoy listening to music, making colored pencil art, playing logic games, keeping up with technology, and walking my dog. Those interests fit naturally with what I like most about data science: creativity, attention to detail, problem solving, and storytelling.

From Math Teaching to Data Science

I knew I loved math as early as sixth grade. The mystery of finding the missing number pulled me in, and by high school I was often the person classmates came to when they needed help. After high school, though, I felt more aimless. I went straight into the workforce and spent time as a customer service representative in a call center. That experience helped me grow as a young adult, especially in communication, confidence, problem solving, and leadership. It also became a turning point that pushed me to return to school and pursue my love of mathematics.

At UT, I fell even more in love with math, especially deeper mathematical thinking and proofs. Through UTeach, I found a path into math education and eventually taught Algebra II and Geometry. Teaching gave me valuable experience explaining complex topics to a wide range of learners and checking not just whether something was said clearly, but whether it was actually understood.

Still, classroom teaching was harder than I expected. I cared deeply about doing the work well, but the workload and stress reached a point where I felt like I was constantly trying to keep up while still falling short of my own standards. I eventually realized I needed to step back and find a professional path where I could keep growing in a healthier and more sustainable way.

After moving to Michigan, I returned to education through tutoring. It was a better fit for that time in my life, but after several years, I wanted something more challenging and more room to grow. I knew I wanted something analytical, but I was not sure what direction to take. When I first spoke with advisors, I thought I might study computer science. Instead, I was guided toward data science, even though I did not fully know what data science was yet.

Once I started learning more, it clicked. Data science took two of my toughest and most interesting areas from UT, programming and statistics, and turned them up to eleven. At first, data visualization was what pulled me in because I loved the idea of making information clearer and easier to understand. Then I learned more about machine learning and the deeper math behind models, and I fell in love with the field even more.

Data science now feels like a natural next step in my journey. It brings together math, programming, statistics, visual storytelling, and communication. My teaching background still shapes how I approach the work: I do not just want to analyze data, I want to explain it clearly enough that people with different backgrounds can understand it and use it.

Why I Started This Blog

I started A Ray of Data as a place to document my learning process publicly while I build my data science portfolio. I want this blog to show not just finished projects, but also the thinking, mistakes, revisions, and lessons that happen along the way.

Part of my goal is to hold myself accountable. Writing about what I’m learning helps me slow down, organize my thoughts, and explain ideas more clearly. That was a big part of teaching, and I believe it is also an important part of becoming a stronger data professional.

This blog will include project walkthroughs, dashboard explanations, technical notes, reflections, and updates as I continue building my skills. I hope it gives future employers, recruiters, friends, family, and even future me a clearer picture of how I learn, solve problems, and grow over time.

What Readers Can Expect

This blog will be a mix of project work, technical notes, and personal reflection. Some posts will be more beginner-friendly, while others will lean more technical depending on the topic. My goal is to make the learning process visible and useful.

Project walkthroughs: I’ll walk through the problem I’m trying to solve, the dataset I’m using, the cleaning steps I take, the modeling choices I make, the visualizations I create, and the lessons I learn along the way.
Dashboard explanations: I’ll share dashboards and explain the story behind the visuals, including what questions the dashboard is meant to answer and how design choices can make data easier to understand.
Technical notes: I’ll use some posts as study notes to explain the math, code, tools, or process behind what I’m learning, especially as I build stronger skills in Python, R, SQL, Power BI, data visualization, and machine learning.
Reflections & Updates: I’ll reflect on past learning, future lessons, mistakes, revisions, and growth as I continue building my skills. I’ll also share updates on current projects and how my portfolio is developing over time.

What I’m Working On

Right now, I’m focused on strengthening the skills I built during my data science degree while also expanding into new tools through online courses and applied projects. My goal is not just to complete courses, but to turn that learning into portfolio work that shows practical skills, clear thinking, and steady growth.

Now: Power BI and Diabetes Readmission Project in Python

One of my main focuses right now is Power BI. I’m currently working through a 30-hour Udemy course that covers all of the skills included in Microsoft’s PL-300 certification, and I’m over 60% of the way through it. I was first introduced to Tableau at the MWC3 conference and immediately enjoyed how visual and flexible dashboard tools can be. Since then, I have also grown to really enjoy Power BI. The visuals are fun to build, and learning tools like Power Query, M, and DAX have felt more approachable than I expected.

After finishing the course, I plan to apply what I learned by creating dashboards based on The Great British Bake Off. I chose this because I love British television, and honestly, who doesn’t love desserts? It also gives me a playful but portfolio-friendly way to practice dashboard storytelling, filtering, visual design, and user-focused reporting.

I’m also working on a larger Python-based project focused on diabetic hospital readmissions. This project is meant to be a research-style report similar in depth to my COVID-19 capstone. I have started the literature review and exploratory data analysis, and I have made solid progress, but there is still more work to do before moving into modeling. My plan is to explore machine learning models that predict whether a patient may be readmitted within 30 days of discharge. I want this project to show not just model results, but the full process: research, cleaning decisions, EDA, feature choices, evaluation, and reflection.

Next: SQL Database Project

SQL is another major skill I want to strengthen. At CMU, I took an introductory database course that covered important theory, but I left wanting more hands-on SQL practice. Last summer, I started a 20-hour Udemy SQL course and made it about halfway through. My goal is to finish the course and then apply what I learn in a complete database project.

My current idea is a small retail database simulation with fantasy branding for fun. The project would involve designing a database from scratch, filling it with sample data, and writing queries, functions, triggers, and procedures. I want it to be creative enough to enjoy building, but structured enough to show practical database skills that could transfer to real business problems.

Blog and Portfolio Writing

As I work toward starting my career in data science, I also want to make consistent time for this blog. I may not publish a new post every week, but my goal is to work on the blog regularly. Writing helps me organize what I am learning, explain my process, and reflect on what worked, what did not, and what I want to improve next.

For my first few posts, I plan to reflect on some of my CMU coursework, break down my current portfolio projects, and explain the learning behind each one. I want this blog to become both a public learning journal and a growing portfolio that shows how I think, build, revise, and keep improving.

Later: Python Course, R Refresh, and Creative Side Projects

Python remains a major long-term focus. I’m about 20% through a 99-hour Udemy data science bootcamp covering Python, machine learning, deep learning, NLP, and end-to-end projects. I plan to return to it after making more progress on Power BI and my current project work.

R is on the back burner for now, but it is still a tool I value. I used it heavily in college, especially for statistics, visualization, and machine learning, and I plan to refresh those skills later because R played a major role in my COVID-19 capstone.

I also want to leave room for creative side projects, including colored pencil art and simple phone photography, because visual thinking and attention to detail are part of how I approach data work too.

Overall, this summer is about disciplined growth. I’m focusing on Power BI, SQL, Python, project work, and consistent writing so I can keep building practical skills and turn that learning into clear portfolio evidence.

Looking Ahead

Now that I have completed my bachelor’s degrees, I’m focused on continuing to learn, building strong portfolio projects, and finding the right entry-level role where I can grow. I’m especially interested in data science, analytics, business intelligence, and related roles that let me use data to solve problems, explain patterns, and support better decisions.

My long-term goal is to become a data scientist and eventually grow into a senior-level role where I can be a go-to expert and mentor for others. I know that kind of growth takes time, practice, and real-world experience, so I’m staying open to roles that help me build a strong foundation first.

I’m especially interested in fields such as insurance, healthcare, education, public data, entertainment, and sports, though I’m open to other areas where data can make a meaningful impact. I’m also open to hybrid, onsite, remote, and relocation-friendly opportunities for the right fit and location.

Within the next five years, I plan to pursue a master’s degree in data science. The exact timing may depend on my career path: if I find the right role, I would like to gain two to three years of professional experience first; if not, I may begin graduate school sooner. Either way, continuing my education is part of my long-term plan.

For now, I’m focused on learning consistently, applying what I learn, and building toward the kind of data career where I can keep growing and eventually help others grow too. Thanks for reading my first A Ray of Data blog! I’d love for you to follow the blog or LinkedIn, leave a comment, or connect as I continue learning and building.

Bonus picture of my dog and husband.

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