Denormalization Strategies
Normalization keeps the database extremely clean, efficient, and consistent, while denormalization intentionally re-introduces redundancy and lowers the number of joins needed to improve query performance.
Denormalization techniques include:
- Materialized Views: Planned and cached data reports that pull data from multiple tables thus cut out the need for complex joins during query processing.
- Adding Redundant Data: Introducing purposefully repeated data in designated situations aimed at reducing join volume while at the same time improving query performance in read heavy system.
Data Modeling in System Design
Data modeling is the process of creating a conceptual representation of data and its relationships within a system, enabling stakeholders to understand, communicate, and implement data-related requirements effectively.
Important Topics for Data Modeling in System Design
- What is Data Modeling?
- Importance of Data Modeling in System Design
- Types of Data Models
- What are Entities, Attributes, and Relationships?
- Data Modeling Notations
- Normalization Techniques
- Denormalization Strategies
- Data Modeling in NoSQL Databases
- Time Series Data Modeling
- Real-world Examples of Data Modeling
- Best Practices for Data Modeling
- Benefits of Data Modeling
- Challenges of Data Modeling
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