Data Governance & Management

Data quality, metadata management, data stewardship

Data governance refers to the policies and processes that define how an organisation manages, protects and uses its data. This means that the data is secure, of good quality and complies with regulations such as GDPT. It ensures data can be transformed from its raw form into a reliable asset that can be used strategically. Data governance is essential in the prevention of data breaches, penalties that will be incurred for non-compliance with regulation, and unauthorised access to data. It enables organisations to make better decisions since business intelligence and AI-powered systems are using more accurate, consistent and reliable data. It reduces the number of redundant processes and increases operational efficiencies, enabling different teams and departments to use the same data.

Metadata is the data about the data, and requires management of its own. This is a foundational infrastructure making data assets discoverable and compliant. It means that both humans and artificial intelligence systems can securely locate and understand information. Metadata management includes technical metadata (which describes system structures like database locations), business metadata (translating technical specs into plain language), operational metadata (tracking the health of data systems) and usage metadata (how data is consumed and who is consuming it).

Data stewardship refers to the way an organisation’s data assets are managed, looking at the way high-level governance policies become daily practice. It protects the quality of data, ensuring that the information an organisation is using for its reporting, analytics and to train AI models is accurate. It strengthens compliance and mitigates against legal risks. It bridges the gap between business, IT and end users. It also improves accessibility, meaning that teams can find and use the data they’re looking for through clear documentation and metadata.