Writing enterprise data definitions is performed as institutions begin to operationalize their data governance. Strategic oversight directs working group attention toward creating definitions for high-demand enterprise data, and the initiative continues iteratively to include more and more data with each cycle of work.
Use this playbook to capture data definitions and create user-friendly data dictionaries for campus decision makers to access.
Section 1: Strategic Focus Areas For Data Definition
Terms commonly used for analysis
At the University of Notre Dame, data governance groups focused on defining a selection of common-use terms to kick off their enterprise data efforts, looking first to build out common definitions for a selection of student enrollment, course registration, faculty, and staff terms.
Sample priority analysis for higher education
Student success analyses are a key component of most higher education analytics efforts, but accurate analysis relies on clean, consistent data. Using specific, desirable student success metrics to guide data definition work can help institutions move faster towards improved outcomes, and therefore generate buy in for expanding and supporting the data governance initiative. We’ve created an example that explores the data definition work that would be required to enable standardized course attendance tracking.
Section 2: Data Definition Processes and Standards
Lightweight definition decision framework
While most institutions expect full attendance at every data governance meeting, the University of Notre Dame takes a different approach. During phases of data definition, committee members choose whether or not to be actively involved in defining each term. Attendance is non-negotiable only for people who are explicitly responsible for terms discussed (propose role) and data governance leadership (document role). Attendance only becomes mandatory for any committee member who opts in. Members who opt out give their tacit agreement to the committee’s decisions.
Key data definition elements
The University of Nevada-Las Vegas’s data dictionary hits all the elements of a skeptic-proof resource that users can understand and trust. The metadata is easily accessible and comprehensible. The data dictionary is web-based, and it can be found on the Office of Decision Support’s website. Users can find it through a search engine and can bookmark the website.
Data definition template
Use our template to define data terms at your institution. Do not only include the term and the definition, but also include further interpretation and usage notes, the kind of values that are acceptable for the term, the mechanism for pulling the term (in technical and nontechnical language), and the review status of the term.
Section 3: Data Dictionary Design Principles
User-centric design principles
Data dictionaries allow users to access, understand, and utilize the context surrounding institutional data, and are a crucial enabler of data-driven decision making. Data dictionaries that are designed with the user in mind will help to improve data governance efforts by making standardization and management of data more impactful across the institution. As the primary foundation for decision-making, it is imperative that data dictionaries follow “user friendly” design principles.
Pop-up metadata
Tying definitions and metadata to reports generated ensures that the appropriate context of enterprise definitions is available during analysis and decision-making processes. To ensure that users have access to appropriate information, Oregon State University makes detailed metadata within every report accessible through clicking on columns and fields.
This resource requires EAB partnership access to view.
Access the tool
Learn how you can get access to this resource as well as hands-on support from our experts through IT Strategy Advisory Services.
Learn More