Working Full-Time While Taking Data Mining: What This Summer Required

This summer just ended, and I am only now starting to understand how much it required from me.

Throughout this summer of 2026, I worked full-time as a Data Analyst at Kewaunee Scientific while taking an accelerated online Data Mining course for my Data Science major at UNC Charlotte. The two responsibilities did not take turns. They overlapped every week, and neither became less demanding because the other one existed.

Going into this summer, the standard was simple to describe and much harder to maintain. Perform at a high level as an analyst. Complete every assignment on time. Maintain an A.

Two Standards at the Same Time

My first priority during the workday was Kewaunee. I was being trusted with real business data, Power BI and Zoho Analytics dashboards, reporting logic, validation work, and requests that other people were waiting on. These were not practice assignments. The numbers and visuals were being used to understand performance and support actual business decisions.

I did not want anyone at Kewaunee to feel the effect of the course load I had chosen to carry. When I was working, the workday belonged to Kewaunee. That meant being present, checking my logic, and making sure the final result was useful instead of simply finished.

Then the workday ended and Data Mining was still waiting.

I also refused to let working full-time become the reason I submitted weak academic work. The course had deadlines of its own, and those deadlines did not care how mentally full the day had already been. I was not trying to survive one demanding responsibility. I was trying to protect the quality of both.

Why an Accelerated Data Mining Course Was Different

An accelerated course compresses the same learning into a much smaller window. There is less time to misunderstand something, recover from a slow week, or tell yourself you will catch up later. Later arrives almost immediately.

Data Mining was not a class I could complete by letting lectures play in the background. The work required me to understand how data should be prepared, how patterns are identified, why a model behaves the way it does, and whether an output is actually meaningful.

I was seeing the professional version of the same problem during the day. A model, metric, or dashboard can look correct while still answering the wrong question. In class, I was learning the methods. At Kewaunee, I was learning how quickly those methods become useless when the definitions, source data, or business context are unclear.

The overlap made the course more relevant. It also made the days mentally heavy. I could spend a workday thinking through reporting logic, close my computer, and immediately switch into an environment where I needed to learn, code, analyze, and submit something before the next deadline.

The hardest part was not always the amount of work. It was the context switching.

What the Days Required

I could not rely on motivation. Motivation is unreliable after a full workday.

I relied on structure. Before each week started, I looked at what Kewaunee required, what the course required, and where the pressure points would fall. Coursework needed a specific place instead of being left for whatever energy remained. Larger assignments had to begin before they felt urgent.

There were plenty of evenings when I wanted to be completely done after work. I had already spent the best hours of the day solving problems carefully, and I still needed to become a student again.

The class still had to get done.

The Standard I Refused to Lower

The most important decision I made this summer was refusing to submit careless work in either place.

At Kewaunee, that meant checking totals, tracing logic, validating fields, and making sure a dashboard did not simply look polished while containing something misleading. In Data Mining, it meant understanding what I was turning in instead of rushing toward a completed status.

That approach takes longer. It also creates work I can stand behind.

I maintained an A in Data Mining through the end of the course while continuing to perform at the level I expected from myself as a Data Analyst. I am proud of the grade, but I am more proud that I did not earn it by becoming unreliable somewhere else. Kewaunee remained the priority during the workday, and my academic work was still completed correctly and on time.

The real accomplishment was holding both standards at once.

What This Summer Taught Me

Capacity is not just about how much work someone can tolerate. It is about how clearly they can decide what matters, how early they can see pressure coming, and whether they can continue producing careful work when convenience disappears.

This summer made me more disciplined because it had to. It taught me to separate focused work from occupied time and showed me that preparation is usually what makes a difficult schedule look manageable. It also proved that I can carry a demanding professional role and an accelerated technical course without lowering the quality of either.

I do not want to romanticize being overloaded. There is a difference between proving that you can handle a difficult stretch and deciding that exhaustion should become your normal state.

Now that this summer is over, I feel proud, relieved, and more confident in what I can handle when the expectations are high.

This summer was difficult. I am grateful I did it well.