Queen's data strategy aims to increase collaboration and utilization of data as an asset to inform decision-making and serve as a cornerstone for digital transformation, innovation, and enablement of analytics. This means data is enabled not only for reporting but can also be leveraged for forecasting, growing enrolment, enabling student success, enhancing efficiency and effectiveness, and drive innovation. Achieving this goal requires a university-wide strategy with an emphasis on data governance, data management and analytics while building a culture of data use and improving data literacy.
The Importance of Having a Queen’s Data Strategy
Data that is governed, trusted and transformed into meaningful information serves as the foundation for timely, effective, and informed decision-making. It empowers individuals to leverage innovation opportunities in digital transformation and AI.
Most organizations experience data challenges like data silos, data duplication across business units, inefficient data flow between departments, disconnected data and analytics platforms, and lack of data maturity and literacy. A data strategy allows us to solve these challenges by making governed data accessible and shared in a secure way, and by building and optimizing platforms and data products that enable use of trusted data for analytics and artificial intelligence.
Key Pillars
The strategic use of data requires a multi-pronged approach. This work is shown as key pillars of the data strategy.
Pillar One emphasizes data governance as a foundational element that guides accountability and data management across the university. It establishes policies, standards, and procedures to ensure data is used, managed, and shared securely.
Pillar Two promotes a data-informed culture where decisions are guided by data insights. It highlights the importance of sharing data, using standardized definitions, and relying on trusted data sources. Achieving this requires ongoing effort, including investing in both technology for data analysis and developing skills to effectively use these tools.
Focuses on building data platforms and data products, data management capabilities, and tools like data catalogues.
Focuses on a data quality framework for ensuring common standards and processes to maintain quality data, data integration from multiple sources, and enablement of data for analytics and AI use.
Key Outcomes
The key outcomes of our data strategy focus on maximizing the value and impact of Queen's data assets to:
- leverage the opportunity to use data for decision-making and insights;
- provide value to constituents and partners;
- develop and share high-quality data products;
- foster trust for all who interact with data;
- empower the data community; and
- build a culture of data use to improve revenue and efficiencies.
Leadership and Operating Model
Data Strategy and Governance Office
Queen's University has established a Data Strategy and Governance (DSG) Office. This office oversees the strategic use of data and currently leads university-wide data governance.
The DSG Office is part of the Office of the CIO and works under the direction of the Data Governance Council (DGC), which is chaired by the Provost and Vice-Principal (Academic). The DGC consists of members of the university's Senior Leadership Team including Vice-Principals, Vice Provosts, Deans and representatives from key departments. The DGC operates through the DGC Sub-Committee (DGCS) and a Data Trusteeship Committee (DTC). For more details about leadership and the accountability model, refer to Council and Committees.
The DSG Office serves a critical enterprise data governance role at the university and includes developing data accountabilities, a stewardship model, a decision-making structure of data councils and committees, data standards and policies, and enabling the use of data for analytics and AI.
For questions about data strategy and governance at Queen's University, contact dsgo@queensu.ca.