Visit Modern Campus

Bringing Data to the Core of Institutional Operations

Bringing Data to the Core of Institutional Operations
While data has great potential for stakeholders institution-wide, very few users actually know how to access that data to put it to effective use.
I’ve been working with data for a very long time and, in all my years of experience, the one thing I’ve learned is that giving someone data only leads to questions. Lots and lots of questions.

No matter what data you give someone, it will always lead to more questions. It doesn’t matter that you gave them exactly what they asked for, now they have more questions. In fact, I’ve come to believe that if I give someone a report and they don’t have questions, they must not be reading the report.

When people look for data to answer a question, they’re really putting forward a hypothesis. Someone thinks that something is true and they want to get the numbers from us to prove that they’re right. However, those numbers often disprove their hypothesis, and then they begin to ask questions to explain why this has occurred. This can go back and forth until either they’ve been proven correct or they no longer care.

So what are we to do? How can we as practitioners of data ever hope to meet our users’ needs?

I believe that instead of focusing on questions they’re asking us, we need to ask ourselves, what data do we have and how can we make it user friendly to query? The people who write applications, the ones that collect all of the data, have no interest in getting data back out of the system. They only care about the collection phase. The way that the data is stored is only meant to improve the performance going in, not coming out. So I believe that our job is to make the data collected available to our users in such a way that they can understand what it means and get the answers they need when they need them.

This isn’t easy and certainly isn’t a technical challenge. Learning how to write structured query language (SQL) is only the first step in a long road of data discovery. Data by itself doesn’t really mean anything. If I tell you seven, what does that mean? Seven days, seven years, what on earth could I mean? This is the crux of the matter. We who work in Business Intelligence can’t be just technicians who know how to write a query. We need to be professionals who know how to find the meaning in the data and convey it to our business users in a way that helps them do their jobs more efficiently and, ultimately, helps companies meet their visions. Especially in education, this is crucial to our end-users’—our students’—success. We all have limited resources to help our students to succeed. And we’re all under increasing scrutiny from politicians and the public who pay our salaries to make sure they’re getting their money’s worth. So it’s critical that in Business Intelligence we allow our staff and faculty to be purposeful and targeted in their efforts to help students succeed.

I see quite often a debate within the Business Intelligence field about Self Service versus Centralized IT and I find it interesting. There is often a perception that our users can’t serve themselves and I understand, but at Arizona State University, I’ve seen users who are amazing and it’s exciting! So often we don’t trust our users. We think they couldn’t possibly understand complex algorithms and databases. In some cases that’s true, but I have found that if you make it easy for them and you support them when they get stuck, they can do amazing things! Our current tool is difficult to use in that it requires you to understand relational databases, sub queries and calculated items which is not for the faint of heart, and yet our users have flourished. Those are skills they will never lose and are invaluable to our organization.

At a certain point, however, we need the subject matter experts to spend more time analyzing the data and less time collecting data. We are trying some new toolsets and hoping that we can get the data to our users in a more user-friendly format so that more and more people can participate in the analysis of data. We all strive for the holy grail of the single version of the truth. Now, if we could just get everyone to agree what that is, we would be all set.

Author Perspective: