Lec-7: What is Data Independence | Logical vs. Physical Independence | DBMS
Data Independence and Data Abstraction
Introduction to Data Independence
- The video introduces the concept of data independence, also referred to as data abstraction, building on previous discussions about the three-schema architecture.
- It emphasizes the purpose of these three levels—view level, conceptual level, and physical level—and their role in achieving data independence.
User Demands and Data Hiding
- Users require constant access to data at any time and place; thus, the system must fulfill this demand while keeping users independent from how data is stored or structured.
- The logical structure of tables (e.g., names, relationships, constraints) is hidden from users to simplify their interaction with the database.
Types of Data Independence
Logical Data Independence
- Logical data independence allows changes at the conceptual level (like adding a new column) without affecting application programs or user views.
- Changes made by one user do not impact what other users see; for instance, if User 1 adds a mobile number column, it does not alter User 2's view.
Implementation through Views
- Views act as virtual tables that present only selected columns to users while hiding others. This maintains simplicity in user interactions despite underlying complexity.
Physical Data Independence
- Physical data independence ensures that changes in physical storage (e.g., moving databases between hard disks or changing storage structures) do not affect the conceptual schema.
Understanding Data Independence in Database Systems
Conceptual and Physical Schema Changes
- Changes in the conceptual schema do not affect application programs, ensuring data independence. Users of web applications remain unaware of any underlying changes.
- Despite significant shifts in data storage over time (e.g., Google), these alterations do not impact the view level for users, maintaining a consistent user experience.
Logical and Physical Data Independence
- Modifications to the physical schema do not alter the conceptual schema, demonstrating logical data independence. Similarly, changes at the conceptual level do not affect the view level.
- Physical data independence allows for backend adjustments without necessitating changes to application programs or user interfaces, enhancing efficiency in data access.
User Experience and Transparency
- Users may experience improved performance through backend optimizations (e.g., switching from sequential search to linked data search), but they will not notice changes in application structure or naming conventions.
- The concept of transparency is highlighted; users feel their data is readily accessible even if it resides remotely. This perception is crucial for user satisfaction.
Continuous Backend Adjustments