Dealing with departmental data silos. Ensuring data quality and security. As data collection and analytics have become increasingly important on college campuses in recent years, IT leaders across higher education have grown accustomed to the challenges associated with data management.
Digital transformation, they’ve learned, can be a complicated and obstacle-filled endeavor; clearing its many hurdles requires skill and patience, and is all but impossible without a strategic plan.
The problem: Many universities, for a variety of reasons, have yet to put such a plan in place. “This work can be kind of conceptual,” says Kelly Briner, director of data governance at Arizona State University. “If you don’t narrow your focus and give it structure, it’s an area where you could really kill yourself trying to boil the ocean.”
Since its launch about five years ago, the data governance program at ASU has provided the framework and served as the “plan” for the university’s approach to data management. Here’s a look at how Briner and others at the institution got that program off the ground, and the key best practices behind their success.
1. Make Maintaining Data Governance Frameworks a Team Effort
Data governance must include ongoing collaboration between all stakeholders, Briner says. “It’s not just about IT,” he explains, “so it can’t be an IT initiative. It has to be a total university initiative.”
According to Briner, two trends that affect everyone on campus are shaping data governance at ASU.
“One is analytics. Like everybody else, we’re trying to be a data-driven organization where decisions are based on facts, not opinions.”
To do that effectively and efficiently, “people have to know what the data means, where it is, and how they can get it.” The other main impetus for the data governance program has to do with concerns around consumer privacy and data protection.
The universitywide policies established through the program provide clear directions for determining, for example, whether information should be made available to the public or be internal-facing only.
“The priority is security and risk minimization, and classifying our data appropriately,” Briner says. “And in order to do that, we have to know where that data is, and everyone has to be involved.”
2. Appoint Stewards to Stick to Data Governance Best Practices
The ASU data governance program has what Briner describes as a “classic structure.” The university president is at the top, with executive sponsors at the next level down.
Their role is to pick a data steward from their direct reports — the senior official within their department who will be responsible for data quality and integrity in their specific area (student data, HR data, financial data, etc.).
“It’s up to the data stewards to approve access to the data, and to know the meaning of the data and how it’s regulated,” Briner says. “They’re the people who are actually in charge.”
3. Establish an Oversight Body for Data Governance Frameworks
To ensure all its data stewards apply the same data management principles to the university data for which they are responsible, most organizations establish an oversight body that has the power to enforce policies and regulations.
At ASU, Briner explains, this body is known as the Data Oversight Council and is chaired by the university’s CIO. Others on the council include nearly a dozen “representative data stewards” and a selection of “expert stakeholders,” like a HIPAA officer and a Family Educational Rights and Privacy Act (FERPA) official.
4. Leverage the Right Data Governance Tools
Data governance teams, Brine explains, can use these tools to build data dictionaries and glossaries customized for their institutions.
“The glossary consists of user-focused definitions of what this data means, like, ‘This is how we define a first-time freshman,’” he says. The data dictionary, on the other hand, is much more focused on IT. “It’s the classic, ‘Here’s a database, it contains these tables, and these tables contain these columns.’”
In their case, Brine says, they originally tried to build their data governance framework on their own. Eventually, however, they decided they could accomplish more by deploying a third-party solution that met their needs.
“It gave us something to coalesce around and really focus on what we wanted to achieve.”
5. Follow Higher Education Leaders in Data Governance
Data governance, in the end, is a “crowdsourcing endeavor,” Briner says. “You’re encouraging people to do something that is not part of their day job for the greater good, with all the challenges that presents.”
Those just starting out, he recommends, should consult the Data Management Association and The DAMA Guide to the Data Management Body of Knowledge, and they should talk with other universities that are already well down the data governance road. “There are leaders in this area people can follow. You can really learn a lot from their experience.”