Melinda Roy
My employment journey to Plaid started in a university bookstore. When I tell people I now work as an analyst in a consulting firm, the first question people have is what education do I have to be in this role. But my education has less to do with my journey than the data literacy skills I picked up in the jobs I had before starting my data analysis career. Looking back, I can see that each role I had before senior analyst taught me skills I might have otherwise underestimated the importance of.
Data literacy is crucial in every role in a higher education institution. Each role requires different skills at different levels, and each has its own tendency to overlook certain aspects of data literacy. In preparing for a formal data governance program, an institution should be aware of and address these gaps through a basic data literacy training program for all employees. A data literate organizational culture is key to the success of a data governance program, and having a strong data governance program is the key to transforming data into a valuable organizational asset.
Data Governance & Employee Skillsets
When you’re introducing data governance and data literacy to your employees, it’s important to recognize the foundation, and often specialty, that exists in each role and office. Data governance is never something developed from scratch, as processes and implicit policies already exist in most organizations at the department or office level. A data governance program makes explicit the standard care and use of the sum total of organizational knowledge about their mission, strategic goals, processes and procedures, data structures, technology, policy and compliance (just to name a few). Data governance thrives when the aggregate level of organizational data literacy is high enough in each knowledge area with an adequate level of skillset required in the role. In other words, data governance thrives in an organization with a strong data culture.
In this series, we’ll explore often-overlooked data literacy knowledge and skills by institutional role and why leadership should first aim to address these gaps before developing a formal data governance framework.
Not every role or office needs to be well-versed in each aspect of data literacy, but they should have a basic understanding of the organizational data language to participate in discussions, know enough about each main aspect of data governance to understand its relationship to their role, and how their relationship to data impacts other roles. We’ll look specifically at: Institutional Research Analysts, Data Entry Clerks, Leadership and Strategic Planners, Enrolment Services and the Registrar’s Office, Instructors and Deans, Information Technology roles, Academic Advising and Financial Aid, Operations and Finance Managers, and Marketing and Recruitment roles. We’ll discuss how each role has a tendency towards expertise, advocacy, or overlooking different aspects of data governance. We'll start with the role I spent the most time in:
Institutional Research Analyst
Research Analysts are experts in analysis of specific modules of institutional data, commonly on enrolment data and student behaviour, though some specialize in other areas like finance or human resources data. They are advocates for data quality, often responsible for identifying and addressing data quality issues before they can proceed with analysis. These roles must know how key data is organized and how to process it, but they can overlook these key aspects of data literacy:
- The processes and challenges of data entry
One risk of being a research analyst is that you are far enough removed from the operation of around data entry that we don’t always know the full extent of what the data means. Analysts who understand data entry procedures can better understand the use, meaning, and critical data validation checkpoints of each data field they use in reporting. With this information, analysts can create data quality management reports to support data cleanup, maintain an accurate data dictionary to support data users across the organization, streamline their data transformation processes, create efficient models, and are better able to contextualize the results of their analysis.
- The policies that define how and what data is collected when
Analysts who understand what data is collected and how can identify overlooked opportunities for data analysis and integration. With this, they can create a vision for deeper and more nuanced research into special topics of concern, stay within and explain the limitations of appropriate data use for analysis or reporting to data end users, and select technology that both suits the data structure and maintains compliance with organizational policy and regulatory compliance standards.
- Communication and Marketing
Analysts are often seen as data experts and can overlook the importance of communication and marketing in their role. With data communication skills, analysts may find themselves asked to give an opinion on what action the analysis dictates, often on decisions that fall outside of the scope of their role. By transforming analysis into accessible and meaningful information, analysts empower data users to be independent decision-makers. In many institutional research offices being able to promote (i.e. market) the use of analytical deliverables such as dashboards and reports, helps ensure not only job stability but can garner financial support for increased technology and human resources, and increase engagement with and reduce redundant data requests for products that already exist. Communicating the institutional research’s office role in strategic planning and management can result in invitations to participate in early stages of these processes, which analysts can leverage to make their future tasks easier—they can influence the development and use of key performance indicators and manage the expectations for new analysis requests stemming from these plans to be fulfilled.
Addressing the existence of these gaps before building a data governance framework can help build relationships between analysts and data entry clerks necessary to have each area understand their responsibility and accountability for specific tasks and knowledge, and improve communicate structures to ensure that a healthy data culture can grow from the ground up.
Interested in learning more about data governance? Plaid is launching a series of workshops for those curious about data governance, those developing a data governance framework development, or leaders looking to advance data governance in their organization. Book a virtual meeting with Andrew to discuss your data governance goals.
Plaid Govern, our metadata management tool specifically designed for higher education institutions, supports data governance initiatives by centralizing data definitions and glossaries, making data lineage transparent and accessible, and facilitating impact analysis so that downstream impacts of changes are minimized. This metadata management tool promotes trust in data by helping users understand where data comes from. Contact us today to learn more about how Plaid Govern can help support campus data governance initiatives.