Which category does "who, what, when, where, why, how" belong to?

Which category does "who, what, when, where, why, how" belong to?

• A. Attribute
• B. Entity
• C. High-quality data
• D. Data relationship

Answer: (C)

The category that includes "who, what, when, where, why, how" is best understood as the framework for defining and understanding data context and requirements. In data management, high-quality data encompasses not only accurate and timely data but also the right context to make data actionable and meaningful. These six questions serve as foundational components in data quality management and serve to guide data requirements. They help ensure that data is relevant, comprehensive, and capable of supporting informed decision-making. Therefore, when considering high-quality data, it’s essential to think about these interrogatives that help clarify the essence and purpose of the data itself, emphasizing that high-quality data is not merely about accuracy but also about effectiveness and utility in various scenarios. The other options focus on different aspects of data management, such as attributes describing characteristics of entities, entities as core components of databases, and data relationships that define how data points are interconnected. However, none of these encompass the broader conceptual questions that facilitate a deeper understanding of data quality and its impact on analytics and business intelligence the way that "who, what, when, where, why, how" does within high-quality data.

The category that includes "who, what, when, where, why, how" is best understood as the framework for defining and understanding data context and requirements. In data management, high-quality data encompasses not only accurate and timely data but also the right context to make data actionable and meaningful.

These six questions serve as foundational components in data quality management and serve to guide data requirements. They help ensure that data is relevant, comprehensive, and capable of supporting informed decision-making. Therefore, when considering high-quality data, it’s essential to think about these interrogatives that help clarify the essence and purpose of the data itself, emphasizing that high-quality data is not merely about accuracy but also about effectiveness and utility in various scenarios.

The other options focus on different aspects of data management, such as attributes describing characteristics of entities, entities as core components of databases, and data relationships that define how data points are interconnected. However, none of these encompass the broader conceptual questions that facilitate a deeper understanding of data quality and its impact on analytics and business intelligence the way that "who, what, when, where, why, how" does within high-quality data.