Analyzing Student Data

In 2020, I worked as a student assistant for the Engineering Department at my university. The department needed help making decisions about hiring professors and planning classes.

They had thousands of students but were making decisions based on guesses instead of data. They needed to know how many students would take each class next semester so they could plan better.

My job was to analyze the data and help them predict this.

Working with Messy Data

The data I worked with wasn’t clean. It was in an old Microsoft Access database that had been used for years.

The data had a lot of problems. Names were spelled wrong. Dates were in different formats. Some records were duplicated.

I spent weeks cleaning up the data. I wrote database queries to fix errors and organize the information. Then I built a model that looked at past trends to predict how many students would take each class.

What It Achieved

My reports helped the department make better decisions.

They could open new sections of popular classes before students registered. They knew exactly where to hire more professors. They avoided having classrooms that were too full or too empty.

This job taught me that working with data is mostly about cleaning and organizing it until you can see the patterns.