I was responsible for making demand projections for the School of Computer Engineering and the School of Civil Engineering using Microsoft Access.
My Experience as Data Analyst Student Assistant at UCAB
In February 2020, I had the opportunity to work as a Student Assistant for the School of Computer Engineering and the School of Civil Engineering at my university. My task was to create demand projections for the upcoming academic year. This was a critical project, as the university would use these projections to make important decisions about resource allocation, such as hiring new professors and purchasing new equipment.
This was my first experience working with a large dataset, and it was a valuable learning opportunity. I was responsible for the entire process, from collecting the data to presenting the final projections. It was a challenging but rewarding experience, and it gave me a newfound appreciation for the power of data.
The Challenge of a Large Dataset
The biggest challenge I faced was the sheer size of the dataset. I had to work with data from thousands of students, spanning several years. The data was stored in a Microsoft Access database, which was not the ideal tool for this type of analysis. I had to find a way to clean, process, and analyze the data in a timely and efficient manner.
Another challenge was the quality of the data. The data was not always consistent or accurate, and I had to spend a significant amount of time cleaning and validating it. This was a tedious but necessary process, as the accuracy of the projections depended on the quality of the data.
From Raw Data to Actionable Insights
I started by collecting the data from the university’s student information system. I then imported the data into Microsoft Access and began the process of cleaning and validating it. I used a variety of techniques to identify and correct errors in the data, such as removing duplicate records and filling in missing values.
Once the data was clean, I began the process of analyzing it. I used a variety of statistical methods to identify trends and patterns in the data. I also used data visualization techniques to create charts and graphs that would help me to understand the data better.
Finally, I used the insights from my analysis to create demand projections for the upcoming academic year. I created several different scenarios, based on different assumptions about student enrollment and retention. I then presented my projections to the deans of the School of Computer Engineering and the School of Civil Engineering.
A Catalyst for Change
The demand projections I created were a catalyst for change at the university. They provided the deans with the information they needed to make informed decisions about resource allocation. As a result of my work, the university was able to hire new professors, purchase new equipment, and make other changes that improved the quality of education for students.
This project was a testament to the power of data-driven decision-making. It showed me that even a simple analysis of a large dataset can have a significant impact on an organization.
Lessons in Data and Decision-Making
My experience as a Student Assistant was a valuable learning opportunity. I learned a great deal about data analysis, project management, and communication. I also learned the importance of data quality and the challenges of working with limited tools.
I am proud of the work I did as a Student Assistant, and I am grateful for the opportunity to have been a part of such a meaningful project. It was an experience that has had a lasting impact on my career, and it has inspired me to continue using my skills to make a positive impact on the world.