A data warehouse is a centralized repository designed to store large volumes of historical and integrated data for reporting, analysis, and decision-making. In data warehousing, the arrangement of data into an appropriate schema is important because it affects query performance, storage requirements, data consistency, and ease of analysis. Two widely used schema designs are the Star Schema and the Snowflake Schema. Both organize data around a central fact table and supporting dimension tables, but they differ mainly in the degree of normalization applied to the dimension data. The Star Schema is one of the simplest and most commonly used designs in data warehousing. In this schema, a central fact table is directly connected to several dimension tables. The structure resembles a star, with the fact table at the center and dimension tables surrounding it. The fact table generally contains quantitative or measurable information, such as sales amount, quantity sold, profit, discount, or number of transactions. It also contains foreign keys that connect it to the related dimension tables. Dimension tables contain descriptive information used to analyze the facts. For example, in a sales data warehouse, dimensions may include Customer, Product,