Breaking Down Data Silos to Create a Comprehensive View of the Student
CT: The Data and Analytics Edition of Educause's Horizon Report recently called out data silos as a pervasive problem in higher education. And the theme of breaking down silos has come up in a lot of Anthology's product announcements, for example, Intelligent Experiences. Could you talk about your focus on connecting the dots between datasets and what that enables?
Milton: The great news is that both of the companies that came together — and even going back to the creation of Anthology — were already working on this problem, and they were working on this problem as it pertained to the heterogeneous environment. For example, Campus Labs, which came together to form Anthology, had been working on this as a way of interconnecting departmental solutions, such as those in student affairs or in academic affairs, into the LMS (whether it was Blackboard or others that are in the marketplace) and starting to create an underlying data lake. With Bb Data, and the work that was going on within Blackboard, there was a tremendous amount of work being done in building out the underlying data lake infrastructure. And now you have that whole ecosystem under one roof.
We're really focused on ultimately building a single view of the learner or constituent — a comprehensive learner record. You've heard that terminology used in the industry — that's been sort of the Holy Grail of breaking down data silos. We're actually doing that. So a lot of heavy lifting is going on within our architecture group, our development group, our product management group, to make that a reality. In a way, the way to think about this is that the solutions all need to be aware of each other. If I have a system over here like an SIS, it's kind of aware of the LMS or the course evaluation toolset or alumni engagement. So I've got a map to Jim Milton as an individual, even though those systems may not have the same kind of data structure. That's what we're creating within our solutions, and we're making sure that it's available to institutions that want to plug into that, as well as to third parties that want to plug into that — it has to be open. We have an access layer — that's sort of the bottom level, which means it's open to various integrations that will occur from other solutions. We have a heavy information layer — if I'm in the student information system, or I'm in the LMS, or I'm in the CRM, there are certain reports that I want to generate or analytics that fit within those areas. And then we have something called the experience layer — that's where the awareness comes in. So I can find out the interactions that have occurred with Jim Milton in this other system and make a more informed decision in the application that I'm in.
One of the ways I would describe this: Imagine you're using Google Maps and you're given multiple routes of how you get from A to B. The preferred route, from a time optimization perspective, is to go down these roads, but maybe it's a toll road and you don't want to pay tolls — so you're given the other option. You now can make a data-informed decision. That's what we mean by Intelligent Experiences — putting more of that information at the fingertips of the decision-maker.
That decision-maker can be a student as well. We gave some examples at the user conference of things that we're working on to bring that home. For instance, helping a student determine what skills they need to focus on in order to get a job in their area of study. That's an example of giving job data, giving micro-credentialing information, and the skills aligned against the course curriculum. I know if I take these courses, I can ultimately be better equipped for that outcome that I'm seeking. You shouldn't have to have an adviser doing that for you — we should provide the tools directly to the student.