What is data governance?
The Data Management Body of Knowledge defines data governance as “the exercise of authority, control and shared decision-making (planning, monitoring and enforcement) over the management of data assets” (DMBOK, 2017) . Put simply, data governance is about implementing a set of policies, processes, structures, roles and responsibilities to ensure that an agency’s data is managed effectively, and that it can meet both its current and future business requirements.
Why is data governance important?
Data governance is as important to an agency as any other corporate, business or IT governance process. It ensures that data is understood, trusted and appropriately used. It ensures that the people who collect, manage and use data understand their responsibilities and see the value it adds to their work, the objectives of the organisation, as well as broader agency outcomes. Data governance is also an exercise in risk management because it allows agencies to minimise risks around the data it holds, while extracting the maximum value from it.
What are the benefits of good data governance?
Data governance, like any other program or process, must have a clear purpose for it to be beneficial. Instead of doing data governance for its own sake, it should be established to help an agency achieve its strategic objectives and it should be closely aligned to their business needs.
When data governance is aligned to the organisation’s needs, it can deliver specific benefits across three areas: business value, efficiency and risk mitigation.
Business Value
- Improved decision-making by ensuring decisions are based on higher quality data
- Increased competitiveness through improved customer satisfaction
- Increased public trust through improved data management and transparency
Efficiency
- Reduction in duplication and waste created by information silos
- Increased data sharing through improved trust and standardisation
- Reduction in costs by improving resource and process efficiencies
- Reduction in time spent by employees finding, acquiring and processing data
Risk Mitigation
- Reduction of risk and costs as data is better managed to support regulatory compliance
- More robust consideration of ethical and privacy issues to avoid reputational damage
Source: Adapted from Information Governance ANZ
Guiding principles of data governance
The NSW Information Management Framework principles should guide agencies in governing and managing their data:
1. Data is business enabling, aligned to business needs and customer outcomes
Data is created and managed so that it directly supports organisational, business and customer requirements. Data is integral to government’s operations and effectiveness.
2. Data is secure, valued and managed as an asset
Data is recognised as a core component of government services and operations, and is supported and maintained as a secure, long-term business asset wherever required.
3. Data is trustworthy, used and reused with confidence
Data is accurate, authentic and trusted, allowing its ongoing use and reuse by government and the community.
4. Data is high quality and (where relevant) spatially enabled
Quality data is of value to customer, business and strategic objectives, and where relevant, spatial enablement allows for improved service planning, delivery and business insights.
5. Data is managed across the full lifecycle, protected from unauthorised use and inappropriate deletion
Data is appropriately managed from procurement or service design, through to creation and to final disposition. This management includes the protection of personal, health and sensitive information, and prevention of deletion until enabled by legal destruction and authorisation.
6. Data is available and open to the community and government
Where appropriate, data is publicly accessible and available in accordance with proactive release and open data principles, or shared within and between organisations to improve policies, services, planning and innovation.
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Last updated 14 Mar 2025