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Building a ‘Super System’ for Student Planning + Income Modelling
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Data-as-a-Service
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Education
Applicable Functions
- Business Operation
Services
- Data Science Services
The Challenge
The University of Nottingham, one of the UK's largest universities, needed to forecast its student population and the related income each year to allocate departmental budgets. The planning and performance team was responsible for collecting and analysing up to nine million records of data on thousands of students across the globe to model expected student numbers and activity accurately. However, with 56 departments requiring deep levels of analytical granularity and five-year forecasts, calculations were complex. By 2015, the team desperately needed a more dynamic student planning model that would allow increased granularity and subsequently improve decision making, whilst working alongside Tableau’s data visualisation. The task would be to handle all reporting for student planning and forecasting as well as verifying data for HESA (Higher Education Statistics Agency), the body that collects quantitative data about higher education in the UK.
About The Customer
The University of Nottingham is one of the UK’s largest universities and research institutes. It is ranked in the top 20 of several major UK league tables and listed in the top 100 universities worldwide. The university has produced many notable alumni and is responsible for many ground-breaking inventions including the MRI scanner. It has a student population of about 45,000 from around the world, spread across multiple campuses in Nottingham and in Malaysia and China. The university has strong links to other universities and companies worldwide and offers over 800 courses covering everything from medicine, science and engineering to social sciences and the arts.
The Solution
The University of Nottingham's planning and performance team initially took advantage of Alteryx to clean and prepare the data for Tableau by completely scrapping the student elements of the data warehouse and rebuilding a new dataset in Alteryx, comprising 10 years of student data. Today, all analysis and forecasting for student planning and funding is performed through Alteryx. The university’s departments are broken down into 56 budget units, all of which want to understand how the 15 different income streams come in. Add 24 student types, all the courses offered and there are over eight billion cells to be modelled. Drilling into the student history reveals current, returning and new student numbers, what they’ll study and expected income from fees and other funding. The team then adds more complex querying to provide deeper insights, such as who’s full- or part-time, undergraduate, postgraduate or postgraduate-research, which students are domestic and overseas, who is joining partway through courses and so on. Once the cycle is complete, the results are transferred to Tableau for checking before reports are distributed to university departments or data is submitted to HESA.
Operational Impact
Quantitative Benefit
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