Data Analytics

Best Practices for Managing Institutional Data

Treating higher ed data like that of enterprises can help institutions meet their goals.

Nori Barajas-Murphy is a higher education ambassador at CDW.

While higher education institutions are primarily dedicated to teaching and learning, they operate with a complexity rivaling that of a large enterprise. From student records and research data to financial transactions and alumni relations, higher education institutions must manage, secure and leverage data streams as diverse and challenging as those in any Fortune 500 company.

Unlike a major corporation, however, higher ed institutions’ data environments tend to be decentralized and disconnected. Data is often duplicated or otherwise unreliable when teams work together because institutions do not have a centralized management strategy.

Establishing a “single source of truth” for institutional data remains a significant challenge in higher education, so a centralized management strategy is the ideal operating state of colleges and universities. As institutions increasingly look for opportunities to employ artificial intelligence technologies in their operations and increase the use of data to inform student success initiatives, centralized data storage will be even more important.

Evaluate Your Current Data Environment

The first step in centralizing data is to conduct a full audit of data sources. Identify where data is housed and who owns and maintains each data set. The data experts at CDW can help institutions take on these complex projects that involve multiple business and academic units to evaluate their current environments to then determine the strategy for data migration and data centralization based on an institution’s academic and business priorities.

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The next step is to gather key stakeholders from various campus departments who own each data source to:

Identify essential existing data for each campus unit
Develop a data map of dependencies
Establish a preliminary structure for centralized data storage

With this data evaluation exercise, determining which products or platforms will meet the needs of each unit will be more reliable.

Determine Goals and Priorities When Migrating Data

Prioritizing the data included in this migration is the next pivotal step and is especially important if you’re aiming to achieve a specific goal or complete a specific project. Consulting with CDW can help you determine where to start. Is enrollment a priority? Start with your data about prospective students. Are you working on improving retention and graduation rates? Focus on data gleaned from learning management systems and other digital learning tools. Are you looking to increase your fundraising efforts? Look into migrating your alumni database.

DISCOVER: Use artificial intelligence to personalize the student experience.

If you’re aiming to undertake a specific project, such as building a feature-rich chatbot, you may need to consider even more strategic prioritization. For instance, you might want to focus on historical call center data and look into common questions from the enrollment management department. Here, financial records or student grades can take a backseat while you focus on the data most relevant to your particular project.

In every instance, the process is similar: identify the problem or goal and determine the best path for a solution.

Select the Appropriate Technology for Your Needs

The key to this is using a robust customer management solution, such as Salesforce or Freshworks. These tools now have the complexity to handle data that can be used across units at an institution. The products do not have to be education-specific; in fact, they shouldn’t be. As mentioned earlier, higher education institutions face the same data complexities as enterprise businesses, so the tools you use should ideally have broad business use cases. Some larger customer relationship management platforms have modules built specifically for higher education purposes, such as student success monitoring or maintaining connections with alumni.

Colleges and universities are places of learning, but they are also businesses and should be treated as such. Holistic and strategic data collection and analysis cannot occur unless all business units are working together with systems that communicate properly, eliminate redundancies and duplicate data, and meet the needs of every department feeding data into them. Despite their different roles and functions, all units ultimately share the common mission of the institution itself, so your data management strategies should reflect that cohesion.

This article is part of EdTech: Focus on Higher Education’s UniversITy blog series.