HOTSPOT - You are reviewing the data model shown in the following exhibit. 

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point Hot Area: 

Box 1: star schema - In computing, the star schema is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. The star schema consists of one or more fact tables referencing any number of dimension tables. The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. Example: 

Incorrect Answers: The data in the question is not normalized. The snowflake schema is a variation of the star schema, featuring normalization of dimension tables. Example: 

Note: A snowflake schema is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions.[citation needed]. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. Box 2: dimension - The star schema consists of one or more fact tables referencing any number of dimension tables. Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-overview https://en.wikipedia.org/wiki/Star_schema https://en.wikipedia.org/wiki/Snowflake_schema https://azure.microsoft.com/en-us/blog/data-models-within-azure-analysis-services-and-power-bi/