How can you tame data sprawl? Consider a chief data officer
August 5, 2024, By Stefanie Chae, Senior Analyst, Product Marketing
-
Learn More
Based on our Office Hours with EAB podcast, Episode 189, How to Tame Data Sprawl
Data challenges are not new to higher education. Data and analytics are critical to the fundamental, institution-sustaining initiatives that will improve retention, enrollment, resource allocation, and academic support. However, at most institutions, data is stored in siloed systems across campus, leaving it largely inaccessible. Matt Logan and Jason Browning, Ph.D. recently sat together for a conversation on EAB’s Office Hours podcast. Dr. Browning spent time researching the role and impact of the Chief Data Officer (CDO) for his doctoral dissertation in Higher Education Administration.
While CDOs are a familiar role in business, the role is newer to higher education. Here are a few highlights from their conversation about CDOs and leadership’s role in taming data sprawl.
-
From the podcast
“There were a few key takeaways I’d love to share, one of those being that there aren’t a lot of chief data officers. At the time of the dissertation in 2021, there were less than 70 chief data officers in higher education, which is so interesting because it’s become a very prevalent role in organizations outside of higher education. It got its start in banking. But we’re seeing more and more institutions [moving] toward the functions of the Chief Data Officer. Even if it really isn’t a full-fledged CDO role, it might be an Executive Director of Institutional Research. It might be an AVP of Institutional Effectiveness, that also has responsibility for supporting the data environment on campus.”
– Jason Browning, EAB Office Hours Podcast, Episode 189
Three ways a Chief Data Officer can help tame data sprawl
Chief Data Officers can help you establish accessible, accurate, and governed data to steer the institution forward. Colleges and universities have started to hire their own CDOs—or elevate the duties of an Executive Director of Institutional Research or Assistant Vice President of Institutional Effectiveness—to work through institutional data challenges as the need for data rises.
Ensure the Officer or Executive leading your data efforts builds relationships and collaborates across campus. These relationships will ensure data is useful, allow conversations to happen organically, and allow you to move beyond data assessment to truly tame data sprawl.
Explore 65 Executive Leaders’ Priorities for Data, Analytics, and Technology
1. Employ data strategically
Chief Data Officers play a role in ensuring data is accurate and governed so other executive leaders can strategize and make data-informed decisions. A CDO can help establish trust in institutional data through the deployment of data governance practices like maintaining a data catalog and helping run data literacy programs at the institution.
2. Reframe ownership of data
Chief Data Officers also play a role in reframing the institution’s approach to data. In a 2023 EAB survey, 75% of leaders described their institutional data as having some systems integrated and others siloed with an additional 15% of leaders describing their system as siloed by department. Reframing data on campus as data belonging to the institution will bolster efforts to build an infrastructure where data from across campus is unified in a central source. Sharing data across departments also supports better decisions. CDOs should facilitate conversation from an organizational perspective to break down barriers while being considerate of security access.
3. Enhance access to data
With the introduction of modern business intelligence (BI) tools and artificial intelligence, low-code tools now allow functional end users to perform robust analysis with institutional data. A Chief Data Officer, by establishing appropriate access and data governance, can help expand access to data across the institution. This collaborative culture can help operationalize strategy much more quickly
Assess data infrastructure
Chief Data Officers should also guide your institution in modernizing its data infrastructure. Data warehouses, data lakes, and BI tools are the components you need to have in place for a strong data infrastructure:
- Data warehousing brings data from disparate sources—such as your student information system, learning management system, customer relationship management, and student success tools—into one central location. Data warehousing ensures that the data environment on campus is more trustworthy and reliable and sets your institution up to move forward as we think about reporting tools, such as Edify.
- Data lakes are the next stage after data warehousing. Data lakes allow room for unstructured data. For example, with a prospective student’s application, their grade point average or standardized testing scores would be considered as structured data while a video essay would be considered as unstructured data. Data lakes allow you to house both the structured and unstructured data.
Strong data warehouses and lakes support your IT, institutional research, and institutional effectiveness teams in creating an efficient data culture and strategy. For example, an effective data environment can help you complete IPEDS and other reporting faster, giving your staff more time to focus on strategic efforts.
Explore Common Data Strategy Frustrations and Aspirations
Data strategy is key
A Chief Data Officer can set and guide your institution’s data strategy to ensure you can rely on, access, and analyze data related to your institution’s mission. Governance and warehousing efforts are important first steps to efficiently providing descriptive analytics about enrollment, program counts, and other mission-critical areas. Once you’ve laid the foundation, reliable and curated data will also be important as you start to think about predictive analytics, AI, and other data and analytics needs in the future.
-
From the podcast
“My primary advice for any institution would be, make sure you have a handle on your situation now […] And particularly as you think about predictive analytics, as you think about AI, as you think about things that are coming at us fast and furious every day, all of those things require clean, reliable, curated data. If you feed unreliable data into those models [or] if you feed unreliable data into an AI chatbot [..], it’s going to generate unreliable data, and that’s going to move downstream, it’s going to be more and more difficult to isolate the impact of that data. And so you want to make really sure that you understand where you are, and that you start with that clean data. And so I think governance efforts are really important. I think warehousing efforts are really important. But I think those descriptive analytics, where we can look at enrollment, we can look at program counts, we can look at that basic data, and make sure we’re near where we need to be before we move on to those exciting next steps is really critical.”
– Jason Browning, EAB Office Hours Podcast, Episode 189
Bring your data together and strategize with Edify.
To speak with a data governance expert or request a demo of Edify, please submit this form.
More Blogs
Inspire better data stewardship across campus. This university shows us how.
Getting your data efforts in order
