Logical data independence and physical data independence are two important concepts in database design and management.
Logical data independence refers to the ability to modify the logical schema of a database without affecting the applications that use the database. In other words, it allows for changes to be made to the structure of the database without requiring changes to be made to the programs that access the data. For example, if a new field is added to a database table, applications that use the database will continue to function without modification as long as they don't rely on the new field.
The importance of logical data independence lies in the fact that it allows for the evolution of a database over time without disrupting the applications that use it. This means that changes to the database can be made to accommodate new requirements or to improve efficiency without causing downtime or requiring extensive changes to the applications that rely on the data.
Physical data independence, on the other hand, refers to the ability to modify the physical schema of a database without affecting the applications that use the database. In other words, it allows for changes to be made to the storage structure of the database without requiring changes to be made to the programs that access the data. For example, if a database is moved to a different storage medium, the applications that use the database will continue to function without modification.
The difference between logical and physical data independence is that logical data independence refers to changes to the logical schema of the database, such as changes to the tables and relationships, while physical data independence refers to changes to the physical storage structure of the database, such as changes to the storage medium or storage format.
Both logical and physical data independence are important because they allow for the flexibility and evolution of a database over time without disrupting the applications that rely on the data. This makes it easier to adapt to changing business requirements and to improve efficiency without requiring extensive changes to the applications that use the data.
