Compare star and snowflake schema ? Power BI interview questions and answers 389

 Compare star and snowflake schema ?

Both star and snowflake schemas are multidimensional models used in data warehouses, but they differ in their structure and how they handle data:

Structure:

• Star Schema: Simpler structure with a central fact table surrounded by multiple dimension tables. Dimension tables directly connect to the fact table through foreign keys. This creates a star-like shape.

• Snowflake Schema: More complex structure with sub-dimension tables nested within dimension tables. This creates a snowflake-like shape with multiple layers of tables.

Data Handling:

• Star Schema:

• Denormalized: Dimension tables may contain redundant data for faster query performance.

• Simpler queries: Easier to write and execute queries due to direct relationships between tables.

• Less storage space: Efficient when dealing with smaller datasets.

• Snowflake Schema:

• Normalized: Reduces redundancy but can impact query performance.

• More complex queries: May require JOIN operations to access data across multiple layers.

• Greater storage space: Larger due to repeated data in sub-dimension tables.

Choosing the Right Schema:

• Star Schema: Ideal for:

• Simple data models with few dimensions.

• Performance-critical applications requiring fast queries.

• Smaller datasets with limited storage space.

• Snowflake Schema: Ideal for:

• Complex data models with many dimensions and hierarchies.

• Scenarios where data integrity and consistency are crucial.

• Larger datasets where storage space is less of a concern.

Additional Considerations:

• Hybrid Approach: Sometimes combining elements of both schemas can be beneficial.

• Data Size and Performance: When choosing a schema, consider the size and complexity of your data, as it affects query performance.

• User Skills: Star schemas are generally easier to understand and manage, making them suitable for less technical users.

Ultimately, the best schema depends on your specific data needs and analysis requirements. Carefully evaluate your data model and choose the schema that optimizes performance, storage, and ease of use for your purposes.

Feel free to ask if you have any further questions about the specific advantages and disadvantages of each schema or need help in determining which one best suits your data structure!