Data Ingestion: Can One Size Really Fit All?



Many institutions find themselves storing their data in aging systems. Often, this leads to disorganized, disparate, inaccessible, or isolated data. These institutions are faced with the challenge of addressing their data and technology issues. In doing so, they may opt to deploy best of breed solutions. Though this may solve some of their challenges, this approach can still fall short of providing students and faculty with systems that allow for optimal data-driven decision making. Ideally, institutions would want to have all their data in one secure location – one source of truth. But is this even possible? Or practical?

Differences and Similarity

Every institution is unique. From programs offered to cohort definition to student body size to demographics, there are at least slight differences. Also, the CRM, SIS, LMS and other systems being used may differ. Even the initiatives institutions undertake will likely vary. Still, one consistency across all institutions is their desire to gain valued insight from their data.

Yet, if an institution’s data systems are disparate, isolated or have shadow data that is collected but never analyzed, how much insight can truly be gained?

Having one source from which to pull data would give a college or university the confidence that its data is valuable and consistent. Can there really be one source of truth, though? Yes, but it will take some work.

It can be achieved, not by an actual physical or virtual source, but by a standard unified data system for the institution. This system will ultimately be a combination of data storage, modeling, definitions, governance, delivery, and reporting.

Not a Data Warehouse

It’s important to note that the unified data solution discussed here is not a data warehouse. The data warehouse will become an architecture where technology and systems deliver data, such as streaming data sources and data lakes. The unified data system will encompass what we know as data warehouses, data lakes, streaming data, and any other data delivery system within or outside the institution.

Benefits of a Unified Source

In higher education, there are numerous internal and public-facing dashboards. When looking at these dashboards we should be asking if the data being displayed is from a single data source (e.g. student information system) or is it from the institution’s unified data. If it’s from a single source, you get only a siloed view. By looking at unified data, though, you’re getting a 360-degree view of key information. It’s a truer way of discovering insight into your programs, students, budgets, etc.

Where to Start?

Assemble a Team

The first step is to create a team focused on data unification. The team should consist of institutional staff whose roles vary as they pertain to the data. There should be a mix of those who deal with data on the back end, the front end, and even somewhere in the middle.

All too often a team like this will be placed under Institutional Research or Institutional Effectiveness. Though this may seem like a fit, be careful. Do your best to keep the team separate so it doesn’t lose sight of its mission. You don’t want it to assume the initiatives of the IR/IE department.

One Problem at a Time

Once a data unification team is formed, move forward with the goal of solving a single problem first. For example, pick an initiative that has a significant impact on your institution, like enrollment, advancement dollars, graduation rates, etc. Avoid the team’s natural thought process to build a full schema for everything. Instead, the team should think about the applications and users of the data. The downstream applications that will leverage this data often only require a select few key fields to perform analytics. Therefore, only focus on the fields that matter to the institution’s initial intended purpose.

Internet of Things (IoT)

As an institution begins forming unified data, there might be a desire to focus on those new shiny streaming sources of data (IoT). Despite all the press, it would be wise to plan for streaming but immediately focus on batch data instead. This is because the majority of an institution’s data is collected and stored in solutions that are batch-focused and not classified as an IoT device.

That being said, a reason an institution would plan for streaming data from IoT devices would be to join and analyze streaming data from campus access control systems against their LMS system. Such a set-up could be used to verify that a student is on campus but not in class.


Use an agile approach to drive the unification of data at your institution. Agile is a proven methodology to build and manage data processes effectively. Agile focuses on the development and delivery of data that is most important to the specific intention you are solving for the institution via your data unification initiative. The agile methodology encourages collaboration between stakeholders and assists with defining the specific problem being solved.


As data systems increase and become broader, there is an even greater need to consider security. The more data that is collected and exchanged, the greater the risk of that data being compromised. While data is being transmitted, it should be encrypted so it can’t be intercepted and used or manipulated without authorization.

The same security risks exist when data is unified as when it’s in disparate systems. But there are security technologies and practices that are easier to enable when working within a unified data system. These technologies and practices should be able to capture all the data requests and consumptions, along with auditing capabilities and control of when and what data is accessible and by whom. Most technologies will demonstrate operational security and compliance around HIPAA and other regulations.

It’s a Process

Technological innovations keep coming – either to join or replace current technology. Predictive analytics, artificial intelligence, machine learning, and cognitive solutions are just a small handful of such innovations making their way into higher education. So, institutions must keep an eye on the present and the future when they begin chipping away at the creation of a unified data system – or source of truth. It’s a process that’ll take time.

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