Which types of data are commonly used in data-driven decision making?

The correct choice encompasses a broad spectrum of data types that are integral to making informed decisions. In data-driven decision making, qualitative data provides insights into behaviors, motivations, and attitudes, which can be crucial for understanding the context and nuances behind the numbers. Quantitative data, on the other hand, supplies measurable metrics that can be analyzed statistically to identify trends and patterns.

Additionally, structured data refers to information that is organized and easily searchable, such as databases with clearly defined fields. This type of data is essential for performing straightforward analyses. Unstructured data, which includes text, images, videos, and more, poses unique challenges but can offer rich insights when analyzed appropriately, particularly through methods like text mining or machine learning.

Combining qualitative, quantitative, structured, and unstructured data allows for a more comprehensive approach to decision-making. By leveraging all these data types, organizations can develop a well-rounded understanding of a situation, leading to more effective strategies and outcomes.