• Ask eAIR
  • 11.16.18

Data Governance Council: Guiding Principles

  • by Liz Novak, Director of Enterprise Systems, Massachusetts Maritime Academy

Ask eAIR invites questions from AIR members about the work of institutional research, careers in the field, and other broad topics that resonate with a large cross-section of readers. If you are interested in writing an eAIR article, or have an interesting topic, please contacteAIR@airweb.org.

This month’s question is answered by Liz Novak, Director of Enterprise Systems, Massachusetts Maritime Academy.

The ideas, opinions, and perspectives expressed are those of the authors, and not necessarily of AIR. 

Dear Liz: My institution is setting up a data governance framework, but we are unsure where to start. I understand Massachusetts Maritime Academy is doing this as well. What guiding principles did your data governance council decide to focus on and why?

We first focused on getting stakeholder buy-in. The success of our data governance project is dependent on many inter-departmental resources, and we needed to motivate our staff to see the benefits of such an initiative. We first invited an Ellucian trainer to speak to our staff and hold departmental focus groups. This allowed staff to discuss their current data climate in a safe environment, learn how data changes made across campus affect other departments, and most importantly, get motivated about the initiative. After this initial investigation on our campus data climate, we chose to focus on the following guiding principles: data ownership, data quality, data access, data security, and data literacy.

Guiding Principles

  • Data ownership
  • Data quality
  • Data access
  • Data security
  • Data literacy

Data Ownership 
(Who is Responsible)

  • Trustees
  • Stewards
  • Custodians
  • Internal data users
  • External data users

Data ownership refers to defining the various levels of responsibility relating to a particular data set. Discussing who is responsible for specific data tasks has already made data maintenance and accuracy simpler for our institution. Similar to the RACI matrix (responsible, accountable, consulted, and informed), we decided to use the titles provided by Ellucian: trustees, stewards, custodians, internal data users, and external data users. Data trustees include staff tasked with high-level policy creating responsibility. Data stewards include the staff managing the data at a more specific operational level, including the responsibility of creating procedures. Data custodians are the IT folks tasked with maintaining and securing the enterprise systems that house the institution’s data. Internal data users includes a spectrum of levels of access to use the data to perform college business. These internal users are tasked with maintaining timely and accurate data entry and reporting via the procedures created by the data stewards. Finally, external data users include any external recipients receiving the data for reporting purposes. 

Data quality refers to the consistency of data values. Working on this principle includes defining the terminology, use, formats, and procedures of specific datasets to ensure accuracy and timeliness. Here we also focus on defining the primary system of record for data sets, as we have many shadow databases aside from our SIS (student information system), such as our Advancement department’s database, the state payroll system, and our Career Services department’s co-op database.

Data access refers to defining the various levels of access needed to retrieve and maintain datasets. Once the levels of ownership and procedures for maintaining quality are defined, we are able to define what levels of access are necessary for each level of ownership. It is the responsibility of the data custodians to create and grant these access levels. Data security refers to the measures taken to ensure this access, preventing any malicious intentions.

Data literacy refers to the understanding of the relevant data stored in our systems. We added this as a principle after our initial focus groups, because we realized how beneficial it is for our staff to understand how interrelated our data is across campus departments. This understanding has motivated and empowered our staff to be energized about the data governance project. Data literacy also includes training specific to our systems. The more our staff understands a system's potential, the more we can streamline and improve our procedures.

While not a guiding principle, we also decided to use the data governance council as a change review board. The council now acts as the official review board for any functional configuration or technical code changes relative to campus-level information systems at the institution. To accommodate this, we schedule time at the end of each council meeting to review any requested changes. This time is also used to discuss solutions to more timely issues relating to data.

Two months into the initiative, we have formed a data governance council, created a project charter, and begun to define these guiding principles around student statuses. Two added outcomes include interdepartmental camaraderie and a mechanism for reviewing historic procedures that may need changing to benefit the institutions efficiency and accuracy of data. Like many institutions, we have a few procedures that have not been changed much once set. Change can be quite hard, but having staff energized about the potential of the initiative has motivated us to review and modify procedures that may have been otherwise stubbornly maintained. I truly believe that the data governance initiative will lead Massachusetts Maritime Academy to a more actively streamlined, procedurally efficient, and accurate data environment.