Data and Analytics Portfolio

We are a Power BI-focused visual analytics team responsible for supporting KPI reporting and self-service analytics across the University. We shape the data analytics landscape, driving informed decision-making, and creating visually engaging dashboards and reports. Our key functions are:

• We collaborate with key stakeholders across the University on the development and delivery of key performance indicators
• We oversee the implementation and maintenance of the Power BI platform and collaborate on other BI tools
• We drive the adoption of self-service analytics across the University by promoting the use of Power BI and other related tools, empowering end-users to generate insights, visualise data and make data-driven decisions

We are responsible for building and maintaining a robust and efficient data infrastructure. We oversee the development, implementation, and governance of DataVaults and Kimball-style data warehouses and data marts. We also drive the adoption of best practices, such as test-driven development, using Azure Data Factory and DBT on Snowflake. Our key functions are:

• We define, develop and implement a data engineering strategy for the University, including the definition and enforcement of data engineering standards and best practices
• We define, develop and implement data governance standards and frameworks
• We drive the adoption of test-driven development methodologies and practices in projects
• We deliver technical solutions
• We manage the technology stack to ensure appropriate tools are adopted and used for data engineering, data integration and data governance

We serve as the product owner for data products within assigned domains, overseeing their development, maintenance, and enhancement throughout the product lifecycle. Our key functions are:

• We collaborate with domain experts, department heads, and senior leadership to understand their data requirements and align data initiatives with their objectives
• We collaborate with cross-functional teams, including data engineers, data scientists, analysts, and software developers, to define product requirements, prioritise features, and ensure timely delivery
• We conduct regular product performance assessments, gather user feedback, and identify opportunities for improvement or new product development
• We define and track key performance indicators (KPIs) to measure the effectiveness and impact of data products, providing regular reports to stakeholders
• We oversee the preparation and submission of key statutory submissions to HESA and the OfS, such as the HESA Student record, HESA Staff record, HESA Provider Profile record, HESA Discover Uni, HESA Aggregate Offshore record and HESES.

We are responsible for developing and implementing advanced data science techniques and methodologies to extract actionable insights from large and complex datasets. Our key functions are:

• We define the vision and strategy for the University’s data science capabilities
• We collaborate with stakeholders to identify opportunities to leverage data science techniques to enhance academic and administrative processes
• We develop and deploy advanced analytical models to uncover patterns, trends, and insights from complex datasets. We build and refine predictive analytical models and apply statistical methods and machine learning algorithms to solve business problems and optimise decision-making processes.