What does data quality encompass?

Data quality primarily refers to the attributes that make data usable and reliable for decision-making. It encompasses several dimensions, including precision and accuracy, which are crucial elements in assessing whether data can effectively support analyses, recommendations, and other outcomes. Precision relates to the level of detail and resolution of the data, while accuracy refers to how close the data is to the true values or the actual state of what it represents. For instance, in geospatial intelligence, having precise and accurate coordinates is vital for mapping and location analysis.

While relevance, volume, and aggregation methods are important in data management and analysis, they do not fully capture the broader spectrum of data quality as defined by precision and accuracy metrics. The choice that focuses on precision and accuracy directly highlights the essential qualities that ensure data can be trusted and leveraged effectively in applications, particularly in fields such as geospatial intelligence where accuracy can have significant implications.