FUNDAMENTALS OF COMPUTER

Detailed explanation-1: -The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. Normalizing attributes results in storage savings, the tradeoff being additional complexity in source query joins.

Detailed explanation-2: -The snowflake schema is a fully normalized data structure. Dimensional hierarchies (such as city > country > region) are stored in separate dimensional tables. On the other hand, star schema dimensions are denormalized. Denormalization refers to the repeating of the same values within a table.

Detailed explanation-3: -Snowflake schemas will use less space to store dimension tables but are more complex. Star schemas will only join the fact table with the dimension tables, leading to simpler, faster SQL queries. Snowflake schemas have no redundant data, so they’re easier to maintain.

Detailed explanation-4: -Databases and schemas are used to organize data stored in Snowflake: A database is a logical grouping of schemas. Each database belongs to a single Snowflake account. A schema is a logical grouping of database objects (tables, views, etc.).

Detailed explanation-5: -Data Management with Star Schema A product attributes table is one example. Star schemas are often implemented in a denormalized fashion, with typical normalization rules relaxed. The advantage of this can be simpler reporting logic and faster performance as data may be stored multiple ways to facilitate queries.