What role do "Fact Tables" play in the Caboodle Data Model?

In the Caboodle Data Model, Fact Tables serve a critical function by storing measurable, quantitative data that is often used for analysis. These tables are designed to capture data related to specific events or transactions, making them essential for business intelligence and analytics purposes. Each entry in a Fact Table corresponds to a particular occurrence, such as sales transactions, patient visits, or service instances, and it typically contains numerical values that can be aggregated or analyzed, such as counts, sums, or averages.

Additionally, Fact Tables are linked to Dimension Tables, which provide context and descriptive attributes related to the measurements held in the Fact Tables. This relationship is crucial for conducting detailed analyses and reporting, allowing users to examine data not just in isolation but also in relation to various dimensions, such as time, geography, or product categories. The design and structure of Fact Tables make them central to data modeling in the healthcare context, where understanding and analyzing quantitative information is vital for decision-making.

The other options do not accurately reflect the function of Fact Tables within the Caboodle Data Model. Non-quantitative data is typically stored in Dimension Tables, while real-time data organization might involve other table structures suited for operational data management. Lastly, while customer feedback may be an important aspect of data analysis