What is a common characteristic of a star schema in data modeling?

A star schema is a type of data modeling that is widely used in data warehousing and business intelligence. The defining feature of a star schema is that it has a centralized fact table, which contains quantitative data for analysis, surrounded by dimension tables that provide descriptive attributes related to the facts.

This centralized structure allows for efficient querying and is designed to optimize the performance of read operations, which is often essential in reporting and analytics scenarios. The straightforward nature of the star schema, with its direct relationships between the fact table and dimension tables, simplifies the data model and makes it user-friendly for analysts.

In contrast to other structures, a star schema avoids complex relationships, as typically seen in snowflake schemas, where dimension tables are normalized into multiple related tables. Hierarchical data structures are not a focus in a star schema; instead, dimension tables are often denormalized to reduce the number of joins needed during queries. Lastly, data normalization is not a characteristic of the star schema, as it often involves a certain level of denormalization to ensure fast query performance and ease of use for business intelligence purposes.