What is Data independency?

The main purpose of the three levels of data abstraction is to achieve data independence. As the database changes and expands over time, it is very important that the changes in one level should not affect the data at other levels of the database. This would save time and cost required while changing the database. So, let's get started and learn more about data independence.

Data Independence

Data independence refers to the property of DBMS through which we can modify the schema definition at any level without changing the schema definition at any higher level. A database has three levels of abstraction as shown in the diagram below.

We have two levels of data independence that are defined on the basis of these three levels of abstraction.

1. Physical Data Independence
2. Logical Data Independence

Physical Data Independence

Physical Data Independence refers to the characteristic of changing the physical level without affecting the logical level or conceptual level. Using this property we can easily change the storage device of the database without affecting the logical schema.

Example: Suppose you want to replace the storage device form hard disk to SSD or magnetic tape then it should not affect the data stored at the logical level.

The changes in the physical level may include changes like:

1. Using a new storage device like SSD, magnetic tape, hard disk, etc.
2. Using a new data structure for storage.
3. Using a different data access method or using an alternative file organization technique.
4. Changing the location(like changing the drive) of the database.

Logical Data Independence

It refers to the characteristics of changing the logical level without affecting the external or view level. This also helps in separating the logical level from the view level. If we do any changes in the logical level then the user view of the data remains unaffected. The changes in the logical level are required whenever there is a change in the logical structure of the database.

The changes in the logical level may include:

1. Changing the data definition.
2. Adding, deleting, or updating any new attribute, entity or relationship in the database.

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