For the past year, Jason Simon, PhD, has been on a journey to fundamentally reengineer the data landscape of the University of North Texas (UNT). Like any large enterprise, UNT is awash in data. Academic data. Business data. Research data. As Assistant Vice President for Data Analytics and Institutional Research, Simon knows the potential of data to drive business and academic outcomes, like student retention rates and student transportation costs. But how does one transform the analytics culture of a century-old institution?

“The biggest challenge facing higher education right now is just trying to wrangle all the information in a way that can actually be used for some really strong purposes,” Simon says.
UNT is home to 38,000 green-clad students, enrolled in more than 100 graduate programs. Since its founding in 1890, the university has been a pioneer in emerging technology.
But like so many others, the institution was data rich and insight poor. Fundamental issues with data integrity, data management and data governance plagued the university’s analytics department, relegating data to silos and making enterprise analytics difficult.

Addressing this challenge meant starting from the ground up, according to Simon.
“Everyone wants to jump automatically to the visualization and the pretty tools,” he says. “But the data must be addressed first. Where does it exist? How do you manage it? What’s the metadata around it? For us, getting our data in order has been our secret sauce.”
Deploying SAS® Data Management brought about a seismic shift in UNT’s analytics capabilities. Now, more than 425 business users across the university are empowered to make decisions based on the UNT Insights program housed on the university’s enterprisewide data and analytics platform. “The data management opportunities that SAS afforded us have been a real difference maker,” Simon says. “It was the shot of adrenaline we needed to reach our goals.”
Armed with a single source of the truth, executives quickly gained the confidence to make policy decisions based on analytics. Success soon followed.

The drop, fail, withdraw, incomplete (DFWI) rate is a key indicator of student success. Administrators track this metric closely, which in years past, was presented on an exhaustive 75-page Excel spreadsheet and available by single semester only.
By harnessing the power of SAS Visual Analytics, administrators were able to view a four-year trend for DFWI rates, exposing patterns to investigate. Policies and procedures were changed, and as a result, retention rates rose across first-time-in-college (FTIC) and transfer populations, leading to better student outcomes and an estimated $450,000 savings for the university.
With a solid data foundation in place, analytics projects began to roll.

One involved optimizing bus routes. Simon and his team were asked to look at where students lived in relationship to campus. Using SAS Visual Analytics, they created a heat map of student housing, which they overlaid on top of transportation routes.
The 30-minute exercise exposed an opportunity to eliminate some of the buses while retaining adequate transportation options. Nearly $450,000 went back in the coffers.
“Sometimes it doesn’t take a 5,000-hour data modeling exercise to yield value from analytics,” Simon says. “People often spend time looking for answers to the really hard, deep, complex questions, but they can miss the opportunities right in front of them.”
According to Simon, “Since implementing SAS, efficiencies afforded by analytics have reduced costs at the university by more than $1 million. Factor in the positive impacts on student success, and you’ve got a strong analytics culture where decision making generates wins on multiple fronts.” Simon is quick to credit the university’s executives for their support.
“We’re really blessed at the University of North Texas to have a leadership team that not only understands the work we’re doing – and is supportive of it – but also isn’t shy about championing it in their own divisions.”

Mobile dashboards give leaders quick insight to make decisions. They used to pick up the phone to get answers from Simon. Now they can drill into the data themselves.

“We’re no longer handing out fish,” Simon says. “Instead we’re helping our community learn how to fish. And the investment is paying off. Our executives are starting to think differently about the kinds of questions they ask, which drives us forward. We are better able to leverage our staff expertise to enable the institution to continue to support our students toward their goals of earning degrees.” Success with analytics has formed a springboard for future projects. Instead of looking externally, UNT has launched a payroll dashboard to analyze, down to paycheck level, every dollar spent at the university. In addition, four new analytics graduate degree programs are being introduced to keep the talent pipeline strong.

“The future of analytics at the University of North Texas is vibrant,” Simon says. “And I cannot overstate the importance of helping institutional leaders use data to drive better outcomes. Data management and data governance are essential building blocks for any institution – and its students – to be successful.”

QUESTION ONE [40]
1.1 From the article, describe the key issues that need to first be address before any analysis can take place. Use your own research to elaborate on the concepts raised. (25)
1.2 Describe the tools that the University of North Texas using to address the challenges they are facing. (5)
1.3 Elaborate on how UNT used Business Intelligence to improve the student retention rate and reduce operational costs. (10)

QUESTION TWO [30]
2.1 Elaborate on the three types of data mining tasks. (15)
2.2 Knowledge discovery on the internet involves the process of extracting valuable insights and patterns from vast amounts of data available online, leveraging advanced algorithms and data mining techniques to transform unstructured information into actionable knowledge.
Examine the factor that contribute to the significant challenges in achieving effective and efficient knowledge discovery on the internet. (15)

QUESTION THREE [30]
3.1 Imagine you are the CTO of a rapidly growing e-commerce company that handles millions of product listings, user profiles, and transaction records daily. Your relational database management system (RDBMS) is struggling with the unstructured nature of data cannot meet the scalability and performance demands of your business.
Customers are experiencing slow response times, and your database administrators are constantly optimizing queries.
Based on your studies suggest and elaborate on a more suitable database structure. (15)
3.2 Virtual assistants, like Siri, Alexa and Google Assistant, have become an integral part of our daily lives, making it easier for us to manage our time, access information, and control our smart devices.
Examine the artificial intelligence techniques that virtual assistants make use of. (15)

Answers to Above Questions on Business Intelligence

Answer 1: An analysis of the given article indicates about the critical issues of data integrity, data management and data governance, and these issues are faced by the University of North Texas in developing a strong analytic culture. It is important to resolve all these issues for achieving reliability in decision making process.