What best describes 'data integrity' within Data Governance principles?

The concept of 'data integrity' within Data Governance primarily refers to the correctness and reliability of data. This means that data must be accurate, consistent, and trustworthy throughout its lifecycle. Ensuring data integrity means that data is free from corruption, errors, or unauthorized modifications, which is crucial for organizations that depend on accurate data for decision-making, reporting, and compliance.

Maintaining data integrity encompasses various practices, including data validation, error checking, and implementing controls to prevent unauthorized changes. Organizations must enforce standards and protocols that uphold data integrity to ensure that stakeholders can rely on the information provided to them.

The other options pertain to different aspects of data management. Reducing data usage can be part of a strategy to optimize data processes but does not address the correctness of data. Data anonymization focuses on protecting personal information and privacy rather than ensuring that the data itself is correct. Limiting data to predefined roles is about access control and security rather than the accuracy or reliability of the data itself. Thus, while all these aspects are important in data governance, they do not directly encapsulate the full meaning of data integrity as the chosen answer does.