Star schema
Simple database design used in data warehousing where a central fact table is connected directly to dimension tables.
Snow flake schema.
Data warehouse schema that organizes data in a logical and normalized way meaning that data is divided into multiple related tables to reduce redundancy and improve data integrity.
Difference between snowflake schema and star schema.
Star schema has Central fact table connected directly to dimension tables while snow flake has central fact table connected to dimension tables, which are further normalized into multiple related tables.
Star schema dimension tables contain redundant data. Snow flake dimension tables are broken into smaller related tables to eliminate redundancy.
Star fewer joins simple queries. Snow flake more joins complex queries.
Star schema faster query performance due to fewer joins. Snow flake Slower query performance due to more joins.
Star schema consumes more storage space. Snow flake requires less storage space.
Star schema easier to understand and design resembles a star shape. Snow flake more complex to understand resembles a snowflake shape.
Advantages of star schema.
Easy for users and developers to understand.
Faster query execution due to fewer joins.
Efficient for OLAP and data visualization tools.
Ideal for data marts and reporting.
Disadvantages of star schema
Redundant data in dimension tables increases storage cost.
Updates or changes in dimensions can cause data inconsistency.
Not ideal for very large or complex datasets.
Advantages of snow flake schema
Reduced data redundancy.
Better data integrity due to normalization.
Easier maintenance updates to dimension data propagate automatically.
Disadvantages of snow flake schema .
Complex queries with multiple joins slower performance.
Harder for business users to understand.
Slightly more difficult to design and maintain.
Where to use snow flake schema.
You have a large and complex database with many hierarchical relationships.
Data consistency and storage efficiency are more important than query speed.
You need a well-organized structure for detailed analysis and reporting.
Where to use star schema.
Data Warehouses and Data Marts.
Business Intelligence and Analytics Platforms.
Management Dashboards and Reporting Systems.
Ad-Hoc Analysis Environments.
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