University of Central Florida (UCF) GEB4522 Data Driven Decision Making Practice Exam 2

Comprehensiveness of the data is essential for ensuring usability because it directly impacts the quality and reliability of the insights derived from that data. Comprehensive data encompasses all necessary dimensions and variables relevant to the analysis, ensuring that decisions made based on this data are well-informed and reflective of the complete picture.

Having comprehensive data means it accurately represents the phenomenon being studied, capturing a wide range of scenarios, conditions, and variations. This breadth allows for more nuanced analyses, reducing the risk of overlooking critical factors that could influence outcomes. When data is sparse or lacks key components, it can lead to misleading results and poor decision-making.

For example, in a business context, comprehensive data about customer preferences, purchasing behaviors, and market trends enables more targeted marketing strategies and improves customer satisfaction. If data were limited in scope, companies might miss out on understanding shifts in consumer interest, leading to ineffective strategies.

While the legitimacy of the source is important for ensuring the data is trustworthy, and the volume and frequency of data collection can contribute to timeliness and relevancy, comprehensive data fundamentally ensures that the insights drawn are robust and applicable across scenarios, enhancing overall usability.