In data governance, what aspect does data integrity refer to?

Data integrity refers to the accuracy and consistency of data over its lifecycle. This concept is crucial in data governance because it ensures that the data being used is reliable and trustworthy for decision-making processes. Data integrity involves maintaining the correctness of data by preventing unauthorized changes, ensuring data consistency across databases, and validating that data accurately reflects the real-world instances or concepts it is meant to represent.

The focus on accuracy means that the data must accurately reflect what it is intended to represent, while consistency ensures that data remains the same across all instances and updates. This fosters confidence in the data for analysis, reporting, and compliance purposes.

The other aspects mentioned—speed of data retrieval, visual presentation, and variety of data sources—are important in the broader context of data management and analytics but do not directly relate to data integrity. Speed pertains to performance metrics, visual presentation deals with how data is displayed, and variety concerns the different forms of data sources, which are all separate from the foundational requirement of ensuring that the data is both accurate and consistent throughout its use.