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Five Themes and Outcomes from the Higher Education Data Warehousing (HEDW) Conference
Posted on April 27, 2015
Author: Kirby Lunger, Performance Architects

The Higher Education Data Warehousing Forum (HEDW), “a network of higher education colleagues dedicated to promoting the sharing of knowledge and best practices regarding knowledge management in colleges and universities, including building data warehouses, developing institutional reporting strategies, and providing decision support,” hosts an annual conference every year for networking and knowledge-sharing purposes.  The event is comprised of training sessions, presentations by universities and select vendors, and a vendor showcase.

Performance Architects has been proud to participate as an invited sponsor of the HEDW Forum for the past five years running, and appreciates the opportunity to teach, learn, and collaborate with such an experienced and talented group of individuals.  We wanted to share our thoughts about the top five trends and outcomes from the HEDW Forum held last week at Illinois State University for our friends and colleagues who weren’t able to attend this year. 

Our team attended at least three or more sessions a day, and held numerous conversations with attendees, so we were able to get a strong overall sense of key trends.  The topics definitely resonate with our first-hand experience working in the higher education and data warehousing markets for the past several years.

Theme #1: Institutions are increasing their use of cloud technologies, especially “private cloud” capabilities.

Several institutions discussed their in-flight projects to move nearly all their infrastructure to cloud-based solutions, although these are mostly “private clouds” (meaning Platform-as-a-Service or PaaS).  This is quite understandable considering the security concerns around the sensitive nature of data involved with many higher education transactional systems, including social security numbers, bank accounts, and other personal information like addresses, phone numbers, etc.

One big surprise for us in this area was a move by several universities from traditional “big software vendor” data warehouses to the Amazon Redshift solution.  Amazon Redshift is a petabyte-scale database which uses columnar storage technology to improve I/O efficiency and parallelizing queries across multiple nodes.  On the downside, Redshift doesn’t provide for stored procedure capabilities, which many small-to-medium-sized universities rely on for their day-to-day operations.  Those who have migrated to Redshift say that this deficit in functionality can be managed effectively through the use of extract, transform and load (ETL) or extract, load and transform (ELT) technologies.

Theme #2: Data discovery tools are a compliment to – but not a replacement for – existing business analytics capabilities and solutions.

Data discovery continues to be a hot topic.  One of the sessions demonstrated the use of Tableau, replacing a Cognos environment.  This was a standing-room-only session as there is a tremendous appetite for the insight and performance capabilities that data discovery provides.

On the downside, tools like Tableau rely on your team to manually extract data from your online analytical processing (OLAP) system (such as Essbase) to produce custom data sets.  You can use these data sets locally or upload them to Tableau’s cloud.  Tableau and its competitors claim their solutions are fast and dynamic, but any solution is faster if you essentially strip away data integration and security capabilities by preparing the data sets manually before you load them into the system!  This reinforces the idea that these tools are best suited as a complimentary solution to – not a replacement for – your current business analytics environment.  To this end, most of the institutions attending the conference saw Tableau and related solutions as “another tool in their arsenal” in addition to the more enterprise-strength business intelligence solutions they already have in place.

Theme #3: Big data is important to understanding key trends in higher education and institutions need to start thinking about solutions in this arena now!

Traditional universities are just entering the realm of big data as they compete with for-profit, online educational offerings (e.g., University of Phoenix) and even not-for-profit institutions with a strong online presence (e.g., Southern New Hampshire University).  These online offerings generate a tremendous amount of data and valuable information.  In addition, schools also maintain inside-the-firewall, web-based learning management systems such as Blackboard and Moodle that generate massive amounts of information including student-teacher and student-student conversation data.

Our presentation at HEDW, “A New Business Analytics Definition: Performance Architects Clarifies Business Intelligence & Data Discovery, Storage, and Integration Confusion,” discusses the big data trend in detail and provides case study examples of ways your institution can get started in this realm.  If you’re interested in obtaining a copy of this presentation, please sign up for our free Learning Center here; the Performance Architects Learning Center is a community and forum that provides access to all of our content, including functional, technical and industry-specific conference and event presentations, webinars, and white papers developed during our many years of experience working with organizations with similar interests and needs.  Performance Architects also recently published another blog entry, “Five Ways to Evolve Your Business Analytics Software Environment to Address the Big Data Revolution,” that discusses actions you can take in this arena.

Trend #4: Increase emphasis on data governance capabilities as a result of the move to the cloud.

Universities need data governance more than ever in order to preserve the “single source of data” for their data warehousing systems.  Most universities maintain multiple data warehouse and business intelligence systems on-premise and in the cloud that are a mix of legacy and current technologies.  While true data governance is a lofty goal for even the most forward-thinking organizations, this represents an idea that universities should be striving towards.

We believe the shift to cloud-based technologies is the main driving force behind this need to update university data governance systems and processes.  Without the capability and maturity in data governance, institutions are challenged in migrating and maintaining information spread across several cloud-based systems.

Trend #5: The integration of the business intelligence (BI) and institutional research (IR) functions continues, with mixed results.

Hank Childers, the Executive Director for University Analytics and Institutional Research at The University of Arizona, discussed a study he conducted with several U.S. institutions about their BI and IR organizational structure.  Although this wasn’t a statistically significant sample, some clear themes emerged from the research.

The first is that this combination of functions is not common across the institutions he surveyed.  Many are still feeling their way to an organizational structure that makes sense at their institution.  This has a lot to do with the different perspectives of these two groups, which are a result of their varying missions and constituencies.  In addition to the cultural differences between the two functions, institutions also appear to be fighting the familiar foes of silo-ed activity, limited enterprise system scalability, and the challenge of big data management, which creates even more barriers to success.

One critical success factor Hank noted is that BI and IR leaders need to cooperate to achieve common goals. Organizations should consider adopting an “agile” philosophy to kick-start any combined BI/IR projects. Specifically, institutions should gather requirements; prototype; collect feedback; iterate; and repeat.  It is often best to consider the idea of starting small while thinking big to deliver quick wins to gain user and leadership endorsement. Success can further hinge on involving both groups in requirements gathering and solution design.

Finally, he maintained that institutions have an opportunity to meld the technology and systems skill sets within BI with the business and user focus of IR to ensure analytics has a “seat” at the leadership table.  It is becoming ever-clearer that good data management and analytics capabilities will influence strategic and tactical decision-making.

In conclusion, HEDW is a thriving conference and forum for those in higher education and data warehousing and we cannot encourage our clients enough to participate in this group.  There are several grants available for those who are unable to secure budget for travel and lodging to this conference.  Next year’s conference will be held in Rochester, NY and we hope to see you there!  The details on the conference aren’t published yet, but will eventually be posted here.

If you’re interested in assistance with any of the topics covered in this blog post, please contact us at sales@performancearchitects.com and we would be happy to set up a time to discuss.

Authors: Kirby Lunger, Richard Maher and John McGale, Performance Architects


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