Universities are home to vast troves of data, which describes everything from student experience to staffing commitments, overall economic performance, and more.
But universities are often divided into several schools, faculties or departments, which means that data can languish in disparate systems or be stored in incompatible formats.
This was the case at La Trobe University in Victoria, a well-established member of the world’s top 400 universities, whose 3,200 staff currently serve the educational needs of more than 38,000 students.
According to La Trobe’s director of data and analytics, Anthony Perera, university management had concluded that data was a critical asset, but found that critical information was spread across multiple incompatible systems.
Perera says many use cases emerged that highlighted the need for better data capabilities, including a desire to improve the university’s student attraction program and ensure it was effective. in its staffing programs. But each of those ambitions was stifled by data issues.
“We wanted to move from a place of retrospective reporting to a place where we used data to become more of a predictive environment, such as helping struggling students and improving their grade point averages,” says Perera. “But a lot of that data was in people’s heads, which meant there was a lot of dependency on individuals.
“We also had inconsistent data from across the organization, so often the numbers didn’t always line up. This meant that most of the conversations we had were about the differences between the metrics rather than the actual problem at hand. »
A long-term strategy
In 2020, the university council had approved a ten-year strategy. This included a digital strategy, at the heart of which was recognition of the important role data would play in the future of the university.
Perera and his team knew that to realize their data ambitions, they would need outside help. They were looking for a partner who could not only help them design and realize their data ambitions, but also improve the overall data capabilities of the university team.
The university selected KPMG as a project partner, having been impressed with its statements regarding its working practices and its commitment to security in the project process – a key requirement given the sensitive nature of the personal data held by the university. ‘university.
“We knew that ultimately students would also have access to the same platform, so we had to protect the enterprise side of things,” says Perera.
The university was also realistic in expecting that its project budget would not allow it to fully realize these ambitions. He worked with KPMG to use MoSCoW (Must, Should, Could, Won’t) prioritization requirements to determine the eventual scope of the project.
“Data as an asset” was a big thing for us, and how we could leverage AI/ML and predictive analytics was a massive inclusion for us,” Perera says. “And KPMG was able to design a solution that offered these features within our budget.”
For example, the university had studied many AI/ML tools. KPMG has demonstrated that adopting Azure’s Synapse unlimited analytics service can meet enterprise data warehousing and big data analytics needs more cost-effectively.
More than just a project
The university was convinced that the solution had to be able to meet future needs, as well as the present.
This led teams at KPMG and the university to work closely together to implement DevOps processes with the aim of anchoring future development capabilities, including the implementation of DevSecOps practices to place security at the heart of software development. Both organizations have also adopted “everything as code” as a core development principle to ensure maximum flexibility to meet future requirements.
“These decisions were made to support the university’s strategic vision, preparing us for the future,” says Perera. “While we had real use cases for ‘now,’ we needed to make sure we didn’t have to come back and ask for more money for redevelopment later.”
Another critical factor in the development of the project was the inclusion of stakeholders from across the university on steering committees, including the University Architectural Review Board, the Platform Team, the change team and the project management team.
Perera says this ensured strong input from eventual users of the platform, who helped ensure it was fit for purpose, and that those users understood the future possibilities of what was being developed. construction. It also reduced turnaround times.
“Stakeholder engagement and integrating people into governance committees was key for us,” says Perera. “Even in the pre-business case, we met with many key stakeholders individually, and KPMG participated in many of those stakeholder conversations.”
Shane Lyell, KPMG Australia’s data and cloud partner, says the engagement ensured stakeholders had a deep understanding of what could be achieved.
“We took the opportunity to showcase the art of the possible and piece together the business issues down to the data platform,” Lyell says.
Quick returns from the partnership
Perera estimates that the entire project – from start to delivery – took 12 months. With project planning complete, KPMG was able to deliver a production-ready landing zone and analysis platform within eight weeks. KPMG documented, socialized, and ratified a detailed solution architecture for the enterprise-scale Azure landing zone using Microsoft’s Cloud Adoption Framework for Azure, and used Azure’s Well Architected Framework to create the data warehouse design and implementation process.
Perera credits the close partnership between the university and KPMG as a key factor in achieving rapid results. KPMG shared expertise in software engineering, cloud development standards, and reusable assets, which helped establish good development practices at La Trobe, which in turn enabled the rapid creation of data ingestion pipelines. data.
“We got good results in a very short time, which we couldn’t have achieved if we didn’t have a tight-knit team at the hip,” says Perera.
The university is now moving into a second phase of the project, which includes the implementation of a master data management strategy and a comprehensive data governance framework, as well as ongoing work to improve the platform. form of data and increase its functionality.
Perera attributes the university’s ability to do continuous work to the transfer of skills. Rather than just prepping and handing over the built platform, KPMG worked closely with the university’s engineering teams and shared responsibilities with them, allowing for a smooth transition at the end of the project. .
“When KPMG left, we had a fully up-to-date group of data engineers who could pick up the slack and make it work,” says Perera. “It was truly a true partnership commitment, as no part of the team was superior to another and we got to the end point by working together.”
This commitment to upskilling has occurred from the design phase through the development and construction phases of the project. It also helped maintain code integrity and data quality throughout development.
A new center of excellence
The project has resulted in what Perera describes as a new center of excellence in data and analytics within the university, which will be needed to ensure that value continues to be generated from data in the framework of the university’s ten-year plan.
The university is doing this in part by developing a new AI-powered proactive chatbot interface that can analyze staff leave entitlements and encourage them to take annual leave, which has been accrued at high levels due to the pandemic. of COVID-19.
“We’re really excited about this because once it’s deployed, it will really showcase the value of data,” says Perera.
KPMG is the sponsor of the iTnews Benchmark Awards 2022.