There is a lot of confusion in higher education about the term “data governance.” Is it the same as data quality or data management? We recently demystified data governance and explained the key pillars of any data governance initiative including data responsibility, data quality, data privacy, and data security.

There’s a lot of confusion in higher education about what data governance is. Is it security, is it policy, is it data quality? In this blog, we demystify data governance for higher education institutions, explore the signs that your institution may have a data governance problem, and examine the key pillars of data governance.

As part of their digital transformation strategy, many institutions are currently either considering or executing a Student Information System (SIS) migration or reimplementation (i.e. an SIS project)—even during the COVID-19 pandemic.  The Enterprise Architect (EA) plays a key role in making the decision between a migration and reimplementation.  Additionally, the EA will play a key role in each stage of an SIS project, from selection of the right product to ensuring a successful project. 

The requirement for data-informed decisions extends across the campus, including academic advising for student success; donor selection for advancement fund-raising campaign; energy conservation and facilities utilization programming; budget allocation and expenditure control. However, each of these examples contains a major assumption—that the underlying data are both trustworthy and the highest quality available.