The same is true here at MVCC, where individual faculty and staff know a great deal about their jobs, but the organization as a whole lacks the collective understanding of the factors that affect the college. One solution to this challenge is Big Data.
The increasing profile and interest in big data is now moving from the private sector to higher education through increased accountability and reporting requirements, performance-based funding, and the national student success agenda. In fact, SUNY’s annual conference last fall was presented with the overarching conference theme of “Big Data.”
A few years ago, I was intrigued when the employment projections said, “7 out of the 10 jobs that will be in demand in 2015 don’t exist yet.” A data scientist is an example of a new job category that is finding employment in big businesses like Amazon, Apple, and Google. Ever wonder how they know what books you might want to read or songs you might want to buy? It’s called data analytics or big data. I recently heard of a petabyte as a unit of computer memory that is 1024 terabytes, which in turn is 1024 gigabytes. I was not surprised that a new category was needed until I later learned that after petabytes, there are exabytes, zettabytes, yottabytes, brontobytes, and, the largest of all, geopbytes – talk about big data!
The collection and analysis of large databases to inform decision-making has been around for some time, but the evolution of the field is rapidly moving toward predictive analytics – using data to not only inform decision-making, but to predict human behavior based on intentional analysis.
Having always worked in community colleges, I’m hesitant to quickly translate business models and trends into the educational sector. However, predictive analytics and big data seem relevant and useful. Consider the following:
- Students shouldn’t have to apply for graduation – we should have enough data to tell them when they’re eligible to graduate, right?
- Why aren’t colleges able to better explain – specifically – swings in enrollment and the reasons for them?
- If we know the factors that put students at risk, why aren’t more interventions done earlier in a student’s educational journey?
- With the right data collection and analysis, shouldn’t colleges be able to STOP doing more things that don’t work and investing more in the things that do work?
- We send so much data to the State and SUNY through mandatory reporting requirements that they know more about us than we do about ourselves.
If you have any questions or comments on this post, please contact me directly at firstname.lastname@example.org.