Part III: Pragmatic Data Governance: Best Practices of Successful Reporting


In their Top 10 IT Issues, 2017, EDUCAUSE identified “data management and governance” as an issue to “improve…the management of institutional data through data standards, integration, protection, and governance.” We suggest the best way to consider data governance is through pragmatism, or practical solutions that consider the human and cultural elements of data use in higher education. Pragmatic data governance can be understood as a series of standard, controlled, and understood processes which give clear stewardship and responsibility. What is “pragmatically governed” includes data definitions, reports and extracts, data requests, data quality, data access, and data system inventory.

In part one of this series, we introduced the importance of accountability and trust to data governance. In part two, we discussed the idea of just-in-time data governance as a method to address the pace of data use. In this posting, we will discuss the best practices for successful data reporting. The fourth part, which concludes the series, will discuss the institutional shifts in culture that occur when clear data governance practices are implemented.

Defining Successful Reporting

“Successful” reporting is more than correct data. In fact, it is more than correct, relevant data.  Successful reporting includes a process. Successful reporting entails a transparent, verifiable, and repeatable process where participants understand their role and carry it out as part of a larger plan.

Successful reporting engages participants within a clear path from question to answer. The first step on this path is to identify the strategic purpose for the request. Next, identify data elements and any filters of interest. After the report is created, the requestor signs off on the report with a formal approval. Documenting all elements in this process improves the chances that subsequent report consumers can re-use this material or confidently modify it to serve a new purpose.  When the context of the original request is preserved, reports can be re-used for other strategic decisions.  A governed approach to this process means that the interactions among the requester, the data expert, and the report writer are recorded. Individuals who play each of these roles are also identified.  In other words, it is not a mystery as to who created a report and why.

Successful reporting also goes beyond agreed-upon processes; it includes a data governance structure that can account for the different priorities, agendas, and outcomes of departments. This means various departments have a clear line of communication to facilitate the goals of the reporting. The data governance structure also includes a shared knowledge base and basic trust in the data being analyzed and produced.

Best Practices for Data Reporting with Pragmatic Governance

These best practices will establish a governed reporting process:

  1. Ask why, not just what. Having a clear picture of why the data is being requested is critical. This will help scope the request in a productive way for those generating the report and those receiving it.
  2. Document the requirements. A record of the required reporting elements creates clear communication across groups and provides a reference point if the requirements change while the report is built. If all parties have self-service access to the requirements while the report is being built, there is greater likelihood of accurate and comprehensive fulfillment of the request.
  3. Engage the requester. Establishing an early and open relationship with the requester keeps lines of communication open. Often, questions and need of clarification occurs in the reporting process. By working alongside the requester, the work needed for successful reporting can operate more in a synchronous fashion. Documenting the conversation between requester and report writer, and publishing that conversation in the same place as the requirements, creates a centralized place for all communication surrounding a report request.
  4. Document definitions, both functional and technical. Data definitions establish credibility and accuracy to reporting. This dictionary should track changes over time and indicate how the definitions are used in different reports.
  5. Engage data stewards in review and approval. A data steward is an expert in the meaning of data, usually within a specialized domain such as Admissions or Financial Aid. Keeping the lines of communication open means keeping stakeholders involved in the process of reporting at each major juncture. This means having data stewards review incremental progress and final reports in order to steer the reporting process in appropriate ways.
  6. Provide easy access to documentation for everyone. Documentation can take many forms. For example, it can include requirements, policies, or templates. Stakeholders, report writers, and data stewards need access to preliminary documentation in the process of reporting. It is important to provide a transparent system to review, amend, approve, and retract documentation in the pathway to reporting.
  7. Link from report directly to a knowledge base. A knowledge base is a repository to store information, which can be either structured or unstructured data. To maintain credibility in reporting efforts, it is important to demonstrate the source of the knowledge, but also provide links directly to the data itself. Linking to the knowledge base in the report itself helps demonstrate credibility in the report.
  8. Encourage feedback from report users. As part of the editing and approval process, gathering feedback from different constituents helps prevent unintentional error, add credibility to the final report, and engage individual expertise.
  9. Build your knowledge base with each new request: Reuse and grow the knowledge. Reports in higher education are often not stand-alone, but are rather part of a regular reporting process or they are cumulative assessments. In an effort to avoid unnecessary repetition and the creation of new work, it is useful to consider how to streamline the processes and use each report as an opportunity to build a larger, more useful knowledge base.
  10. Collaborate and share knowledge and standards with other institutions and agencies. Academe often works in silos, but awareness of this problem helps create bridges between departments, schools, and reporting agencies. Active collaboration between entities helps aid the reporting process by creating good faith efforts to help one another. Additionally, transparency when possible helps cultivate positive relationships, increase accuracy in reporting, and build one’s knowledge base even larger.


The Data Cookbook and Successful Reporting

The Data Cookbook can be used to achieve all ten listed best practices for successful reporting. As a reporting tool, the Cookbook provides transparent data quality rules and monitoring for all parties. For example, through a Cookbook license, all parties involved the in the reporting process can look at the same workflow, so all involved parties can visually see the progression of reporting from request to fulfillment. Built-in features like valid values references and mappings help clarify the reporting process. Additionally, the Collaboration feature lets a report builder ask any Cookbook user for help with a specific part of the report. Collaboration lets the report writer bring in an expert to help him/her in an ad hoc way because the helper does not need to be part of the formal process. This provides a way to get an expert into the situation for a quick consult without being burdensome or time-consuming to the person tapped.

The Cookbook acts as a knowledge base to store definitions and their pertinent data, as well as a clear record of the reporting requirements in the specifications feature. The Cookbook helps serve as a pragmatic data governance tool by allowing multiple parties to track a report from request to fulfillment.


By James E. Willis, III, Brenda Reeb, and Brian Parish





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