Universities are some of the most complex enterprise organizations. It is no surprise that they have always been interested in using technology to improve knowledge and better control operations. The challenge is that large and complex organizations can take time to change and to leverage the latest technology for enterprise reporting. The recent growth of modern applications and cloud infrastructure has created a rapid change in the ability of academic institutions to obtain useful information. To understand that change, this blog post will take a brief look at the history of enterprise reporting software and what to look for today.

In the Beginning

Universities were some of the first enterprises to get mainframe computers. This makes sense, given that computers were primarily used by researchers, engineers, and scientists – all of whom had a significant presence on university campuses. Applications on these computers were very limited due, in part, to the limitations of early hardware and software.

As applications expanded, they focused on particular areas, such as general ledger and student enrollment. Reporting output was also limited. Line printers were the most common option. They could print a single line of text at a time with very basic text options. The growth of Unix servers and relational databases (RDBMS) in the ‘80s led to the ability to manipulate much more data – and to do it faster. The combination of that and improved graphics in laser printers led to better reporting. Reports could now take the higher volume of data and display it in tables and charts.

Enter the PC

As computing becomes more powerful and RDBMS’s spread, the 1980s saw another advance: the Personal Computer (PC). Suddenly, universities found themselves with data in many places but without the controls of the mainframe model. The “killer app” for enterprises on the PC was the spreadsheet. Made even more prevalent by the growing presence of Microsoft Excel, spreadsheets allowed managers to handle their own data. They could do basic calculations on rows and columns, format key data, and then quickly print out the results. As with the mainframe, data on Unix servers was often duplicated among multiple applications that didn’t interact. Also, where a university might only have a single mainframe, the spread of Unix meant that data was now often on entirely separate computers, making consistency very difficult to achieve. If the numbers didn’t match, it would lead to substantial uncertainty about the accuracy of the data and the overall status of the enterprise.

ERPs, Data Warehouses, and Business Intelligence Tools

The response to the challenge of using multiple, disparate systems was the creation of enterprise resource planning (ERP) systems. The focus was to begin to integrate data, “data dump,” from multiple systems and to create, then share, a data model that provides a clear, consistent view. As data became more complex and varied, the need to analyze and use reporting tools for data became even greater. ERPs saw strong growth in the 1990s.

Along with the growth of ERPs came a rise in data warehousing. This was in an attempt to create a “single source of data” – something that was very difficult to do in the increasingly distributed world of computing. In parallel with the growth of ERP systems was the emergence of the business intelligence (BI) industry. The result was products that could access data from multiple sources using more complex analytics, than what was available in departmental applications or spreadsheets, and use business intelligence tools. The reports, while more complex, were still primarily printed reports that served as static snapshots of periodic information.

Art of Dashboard Design 

As the windowed operating systems (Microsoft and Apple) grew in the late 1990s and the first decade of this century, so did graphics display capabilities. Then a hardware breakthrough arrived. Graphical processing units (GPUs) weren’t a new idea, but in 1999, Nvidia created what is now considered the first modern form. It allowed for far more control of graphics presented on the screen. While the GPU was initially aimed at the computer gaming industry, business software – especially the BI sector – quickly took note. The performance of advanced graphics, combined with analytics and other reporting tools, led to the development of dashboards. The art of dashboard design includes sets of graphical information that provide a quick and easy way to view and understand data. They’re often used by managers, who access the dashboards from their computers or devices. This development then led to the second generation of BI tools, which have been adopted by most enterprise organizations over the last fifteen years. From there, managers can completely customize settings, including picking the best font for dashboard or the layout that works best for their institution.

The Cloud

For most of what we’ve discussed so far in regard to enterprise reporting, connections and communications between different computers occurred in a controlled environment within an enterprise’s facilities. This is commonly called on-premises computing. Technology improvements in networking, hardware, and software, have created a new model where the computing servers can sit in a hosted environment using multi-processor and server technology. This is cloud computing. Its birth and growth have allowed enterprises to do two critical things:

  • Switch a significant portion of capital expenditures to operational expenditures
  • Allow those operational expenditures to rise and fall on demand

Cloud computing has become increasingly popular within numerous industries and has begun taking a foothold in higher education as well. One reason for this is the advantages the cloud extends into the realm of enterprise reporting. Far more powerful analytics and in-depth visualizations can be provided by cloud-based applications, enabling an even clearer picture of the organization. Cloud computing also allows for more rapid development and adoption of analytics-based enhancements.


The evolution of technology – both hardware and software – has helped break down the information silos at higher education institutions. It has provided both departmental and executive management with the ability to receive timelier, more actionable information for enterprise reporting. The combination of text, visual reports and analytics have provided a faster way to see and understand the data institutions need to make key decisions. While the growth of cloud computing is certainly the latest step in that evolution, it most certainly won’t be the final step!

Peter Wilbur

Peter Wilbur is a Technical Product Manager with Evisions and is based out of the company headquarters in Irvine, CA. Peter graduated from Northern Arizona University with a computer science degree in 1984. After working in several industries and with numerous companies, he joined Evisions in 2010 working on the support desk before moving to Professional Services, where he eventually came to serve as Professional Services Manager. Peter is a member of the Project Management Institute and a PMP. He enjoys data visualization and is pursuing a certificate in data science.
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