Data Warehousing - Fact and Dimension Tables
Exploring Fact and Dimension Tables
Fact and dimension tables are fundamental components of data warehousing that organize data into a structured format for analysis and reporting.
Key Points:
- Fact Table: Contains measurable and numeric data (facts) for analysis.
- Dimension Tables: Contain descriptive attributes (dimensions) that provide context to the facts.
- Fact tables are typically normalized, while dimension tables are denormalized for faster queries.
Components of Fact and Dimension Tables
Fact Table: Stores transactional data and numerical metrics (e.g., sales, revenue).
Dimension Tables: Provide context to the data in fact tables with descriptive attributes (e.g., time, product, location).
Advantages of Fact and Dimension Tables
Optimized Query Performance: Denormalization in dimension tables speeds up queries.
Scalability: Allows for scalability by adding more dimensions or facts.
Flexibility: Supports complex data relationships for detailed analysis.
Use Cases
Fact and dimension tables are essential in business intelligence (BI) applications, decision support systems, and data analysis where structured data is crucial for insights.
Conclusion
Understanding the roles of fact and dimension tables helps in designing efficient data models that support analytical queries and reporting in data warehousing.