These projects are often started in either an IR or IT office and tend to be one-sided definitions. IR offices tend to capture only the functional definition, while IT offices tend to capture only the technical definition. The goal should be to tackle both the functional and technical definitions in data dictionaries.

Once an IR office or registrar agrees on the definition for “first-time freshman,” the process of extracting data to define the term should be documented to ensure it is accurate and repeatable; this might include multiple technical definitions.

How do you pull the necessary data from the transactional student system? How do you pull the necessary information from the data warehouse? Is there a different definition for different time contexts (such as “current” or “as of a given date”)?

Data governance: Create structured collaboration

It is not surprising to find half a dozen different definitions for “student” on a campus. The interesting thing is that all of these definitions can be correct; they are just used by different departments in different contexts.

The bursar’s office, the admissions office, and the state government all have different ways of identifying a “student.” When creating a data dictionary, recognize and structure these different points of view. Create a data governance community to allow for “approved” or “official” definitions in different functional areas.

Data stewards can moderate an institution’s conversations about data when assigned to areas like academic records, admissions, HR, and financial aid.

These data stewards should be responsible for approving all terms in their area.

Outside of data definitions, data stewards also can take on critical roles in data quality and data security. Leadership of the data stewardship community should be shared between IT and IR, because they have a role to play for both departments. A collaborative environment with a data stewardship community will help to create a culture of trust and buy-in for data usage.

Data knowledge: Democratize user access

For any individual, the biggest indicator of success in a reporting project is knowledge of both the data structures and business needs. Many campuses have super-users who, over time, have developed a deep understanding of the data systems.

Super-users often gain this knowledge from a combination of timing, circumstances, and specific project assignments. These individuals are very valuable to a campus, but they’re also frequently bottlenecks or silos for access to information.

When I started out in higher-education technology, I was lucky enough to work on multiple data migration projects that forced me to learn the data structures.